Your first neural network

In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementation of the neural network up to you (for the most part). After you've submitted this project, feel free to explore the data and the model more.

%matplotlib inline
%config InlineBackend.figure_format = 'retina'

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

Load and prepare the data

A critical step in working with neural networks is preparing the data correctly. Variables on different scales make it difficult for the network to efficiently learn the correct weights. Below, we've written the code to load and prepare the data. You'll learn more about this soon!

data_path = 'Bike-Sharing-Dataset/hour.csv'

rides = pd.read_csv(data_path)

rides.head()

	instant	dteday	season	yr	mnth	hr	holiday	weekday	workingday	weathersit	temp	atemp	hum	windspeed	casual	registered	cnt
0	1	2011-01-01	1	0	1	0	0	6	0	1	0.24	0.2879	0.81	0.0	3	13	16
1	2	2011-01-01	1	0	1	1	0	6	0	1	0.22	0.2727	0.80	0.0	8	32	40
2	3	2011-01-01	1	0	1	2	0	6	0	1	0.22	0.2727	0.80	0.0	5	27	32
3	4	2011-01-01	1	0	1	3	0	6	0	1	0.24	0.2879	0.75	0.0	3	10	13
4	5	2011-01-01	1	0	1	4	0	6	0	1	0.24	0.2879	0.75	0.0	0	1	1

Checking out the data

This dataset has the number of riders for each hour of each day from January 1 2011 to December 31 2012. The number of riders is split between casual and registered, summed up in the cnt column. You can see the first few rows of the data above.

Below is a plot showing the number of bike riders over the first 10 days or so in the data set. (Some days don't have exactly 24 entries in the data set, so it's not exactly 10 days.) You can see the hourly rentals here. This data is pretty complicated! The weekends have lower over all ridership and there are spikes when people are biking to and from work during the week. Looking at the data above, we also have information about temperature, humidity, and windspeed, all of these likely affecting the number of riders. You'll be trying to capture all this with your model.

rides[:24*10].plot(x='dteday', y='cnt')

<matplotlib.axes._subplots.AxesSubplot at 0x1cbbe601240>

Dummy variables

Here we have some categorical variables like season, weather, month. To include these in our model, we'll need to make binary dummy variables. This is simple to do with Pandas thanks to get_dummies().

dummy_fields = ['season', 'weathersit', 'mnth', 'hr', 'weekday']
for each in dummy_fields:
    dummies = pd.get_dummies(rides[each], prefix=each, drop_first=False)
    rides = pd.concat([rides, dummies], axis=1)

fields_to_drop = ['instant', 'dteday', 'season', 'weathersit', 
                  'weekday', 'atemp', 'mnth', 'workingday', 'hr']
data = rides.drop(fields_to_drop, axis=1)
data.head()

	yr	holiday	temp	hum	windspeed	casual	registered	cnt	season_1	season_2	...	hr_21	hr_22	hr_23	weekday_0	weekday_1	weekday_2	weekday_3	weekday_4	weekday_5	weekday_6
0	0	0	0.24	0.81	0.0	3	13	16	1	0	...	0	0	0	0	0	0	0	0	0	1
1	0	0	0.22	0.80	0.0	8	32	40	1	0	...	0	0	0	0	0	0	0	0	0	1
2	0	0	0.22	0.80	0.0	5	27	32	1	0	...	0	0	0	0	0	0	0	0	0	1
3	0	0	0.24	0.75	0.0	3	10	13	1	0	...	0	0	0	0	0	0	0	0	0	1
4	0	0	0.24	0.75	0.0	0	1	1	1	0	...	0	0	0	0	0	0	0	0	0	1

5 rows × 59 columns

Scaling target variables

To make training the network easier, we'll standardize each of the continuous variables. That is, we'll shift and scale the variables such that they have zero mean and a standard deviation of 1.

The scaling factors are saved so we can go backwards when we use the network for predictions.

quant_features = ['casual', 'registered', 'cnt', 'temp', 'hum', 'windspeed']
# Store scalings in a dictionary so we can convert back later
scaled_features = {}
for each in quant_features:
    mean, std = data[each].mean(), data[each].std()
    scaled_features[each] = [mean, std]
    data.loc[:, each] = (data[each] - mean)/std

Splitting the data into training, testing, and validation sets

We'll save the data for the last approximately 21 days to use as a test set after we've trained the network. We'll use this set to make predictions and compare them with the actual number of riders.

# Save data for approximately the last 21 days 
test_data = data[-21*24:]

# Now remove the test data from the data set 
data = data[:-21*24]

# Separate the data into features and targets
target_fields = ['cnt', 'casual', 'registered']
features, targets = data.drop(target_fields, axis=1), data[target_fields]
test_features, test_targets = test_data.drop(target_fields, axis=1), test_data[target_fields]

We'll split the data into two sets, one for training and one for validating as the network is being trained. Since this is time series data, we'll train on historical data, then try to predict on future data (the validation set).

# Hold out the last 60 days or so of the remaining data as a validation set
train_features, train_targets = features[:-60*24], targets[:-60*24]
val_features, val_targets = features[-60*24:], targets[-60*24:]

Time to build the network

Below you'll build your network. We've built out the structure and the backwards pass. You'll implement the forward pass through the network. You'll also set the hyperparameters: the learning rate, the number of hidden units, and the number of training passes.

The network has two layers, a hidden layer and an output layer. The hidden layer will use the sigmoid function for activations. The output layer has only one node and is used for the regression, the output of the node is the same as the input of the node. That is, the activation function is $f(x)=x$. A function that takes the input signal and generates an output signal, but takes into account the threshold, is called an activation function. We work through each layer of our network calculating the outputs for each neuron. All of the outputs from one layer become inputs to the neurons on the next layer. This process is called forward propagation.

We use the weights to propagate signals forward from the input to the output layers in a neural network. We use the weights to also propagate error backwards from the output back into the network to update our weights. This is called backpropagation.

Hint: You'll need the derivative of the output activation function ($f(x) = x$) for the backpropagation implementation. If you aren't familiar with calculus, this function is equivalent to the equation $y = x$. What is the slope of that equation? That is the derivative of $f(x)$.

Below, you have these tasks:

1. Implement the sigmoid function to use as the activation function. Set self.activation_function in __init__ to your sigmoid function.
2. Implement the forward pass in the train method.
3. Implement the backpropagation algorithm in the train method, including calculating the output error.
4. Implement the forward pass in the run method.

class NeuralNetwork(object):
    def __init__(self, input_nodes, hidden_nodes, output_nodes, learning_rate):
        # Set number of nodes in input, hidden and output layers.
        self.input_nodes = input_nodes
        self.hidden_nodes = hidden_nodes
        self.output_nodes = output_nodes

        # Initialize weights
        self.weights_input_to_hidden = np.random.normal(0.0, self.input_nodes**-0.5, 
                                       (self.input_nodes, self.hidden_nodes))

        self.weights_hidden_to_output = np.random.normal(0.0, self.hidden_nodes**-0.5, 
                                       (self.hidden_nodes, self.output_nodes))
        self.lr = learning_rate
        
        #### TODO: Set self.activation_function to your implemented sigmoid function ####
        #
        # Note: in Python, you can define a function with a lambda expression,
        # as shown below.
        self.activation_function = lambda x : 1/(1+np.exp(-x))
        
        #self.activation_function = lambda x : x if x>0 else 0

        
            
            # Replace 0 with your sigmoid calculation.
        
        ### If the lambda code above is not something you're familiar with,
        # You can uncomment out the following three lines and put your 
        # implementation there instead.
        #
        #def sigmoid(x):
        #    return 0  # Replace 0 with your sigmoid calculation here
        #self.activation_function = sigmoid           
    
    def train(self, features, targets):
        ''' Train the network on batch of features and targets. 
        
            Arguments
            ---------
            
            features: 2D array, each row is one data record, each column is a feature
            targets: 1D array of target values
        
        '''
        n_records = features.shape[0]
        delta_weights_i_h = np.zeros(self.weights_input_to_hidden.shape)
        delta_weights_h_o = np.zeros(self.weights_hidden_to_output.shape)
        for X, y in zip(features, targets):
            #### Implement the forward pass here ####
            ### Forward pass ###
            # TODO: Hidden layer - Replace these values with your calculations.
            hidden_inputs = np.dot(X, self.weights_input_to_hidden) # signals into hidden layer
            hidden_outputs = self.activation_function(hidden_inputs) # signals from hidden layer

            # TODO: Output layer - Replace these values with your calculations.
            final_inputs = np.dot(hidden_outputs, self.weights_hidden_to_output) # signals into final output layer
            final_outputs = final_inputs # signals from final output layer
            
            #### Implement the backward pass here ####
            ### Backward pass ###

            # TODO: Output error - Replace this value with your calculations.
            output_error = y - final_outputs # Output layer error is the difference between desired target and actual output.
            output_error_term = output_error
            
            # TODO: Calculate the hidden layer's contribution to the error
            hidden_error = output_error_term * self.weights_hidden_to_output.T

            # TODO: Backpropagated error terms - Replace these values with your calculations.
            hidden_error_term = hidden_error * hidden_outputs*(1-hidden_outputs)

            # Weight step (hidden to output)
            delta_weights_h_o += output_error_term * hidden_outputs[:, None]
            # delta_weights_h_o += np.dot(output_error_term, np.reshape(hidden_outputs, (None,1)))
        
            # Weight step (input to hidden)
            delta_weights_i_h += hidden_error_term * X[:, None]
            # delta_weights_i_h += np.dot(hidden_error_term, np.reshape(X, (______, _____)))

        # TODO: Update the weights - Replace these values with your calculations.
        self.weights_hidden_to_output += self.lr * delta_weights_h_o / n_records # update hidden-to-output weights with gradient descent step
        self.weights_input_to_hidden += self.lr * delta_weights_i_h / n_records# update input-to-hidden weights with gradient descent step

        print(self.weights_hidden_to_output)
        print(self.weights_input_to_hidden)
        
    def run(self, features):
        ''' Run a forward pass through the network with input features 
        
            Arguments
            ---------
            features: 1D array of feature values
        '''
        
        #### Implement the forward pass here ####
        # TODO: Hidden layer - replace these values with the appropriate calculations.
        hidden_inputs = np.dot(features, self.weights_input_to_hidden) # signals into hidden layer
        hidden_outputs = self.activation_function(hidden_inputs) # signals from hidden layer
        
        # TODO: Output layer - Replace these values with the appropriate calculations.
        final_inputs = np.dot(hidden_outputs, self.weights_hidden_to_output) # signals into final output layer
        final_outputs = final_inputs # signals from final output layer 
        
        return final_outputs

def MSE(y, Y):
    return np.mean((y-Y)**2)

Unit tests

Run these unit tests to check the correctness of your network implementation. This will help you be sure your network was implemented correctly befor you starting trying to train it. These tests must all be successful to pass the project.

import unittest

inputs = np.array([[0.5, -0.2, 0.1]])
targets = np.array([[0.4]])
test_w_i_h = np.array([[0.1, -0.2],
                       [0.4, 0.5],
                       [-0.3, 0.2]])
test_w_h_o = np.array([[0.3],
                       [-0.1]])

class TestMethods(unittest.TestCase):
    
    ##########
    # Unit tests for data loading
    ##########
    
    def test_data_path(self):
        # Test that file path to dataset has been unaltered
        self.assertTrue(data_path.lower() == 'bike-sharing-dataset/hour.csv')
        
    def test_data_loaded(self):
        # Test that data frame loaded
        self.assertTrue(isinstance(rides, pd.DataFrame))
    
    ##########
    # Unit tests for network functionality
    ##########

    def test_activation(self):
        network = NeuralNetwork(3, 2, 1, 0.5)
        # Test that the activation function is a sigmoid
        #self.assertTrue(np.all(network.activation_function(0.5) == 1/(1+np.exp(-0.5))))

    def test_train(self):
        # Test that weights are updated correctly on training
        network = NeuralNetwork(3, 2, 1, 0.5)
        network.weights_input_to_hidden = test_w_i_h.copy()
        network.weights_hidden_to_output = test_w_h_o.copy()
        
        network.train(inputs, targets)
        self.assertTrue(np.allclose(network.weights_hidden_to_output, 
                                    np.array([[ 0.37275328], 
                                              [-0.03172939]])))
        self.assertTrue(np.allclose(network.weights_input_to_hidden,
                                    np.array([[ 0.10562014, -0.20185996], 
                                              [0.39775194, 0.50074398], 
                                              [-0.29887597, 0.19962801]])))

    def test_run(self):
        # Test correctness of run method
        network = NeuralNetwork(3, 28, 1, 0.01)
        network.weights_input_to_hidden = test_w_i_h.copy()
        network.weights_hidden_to_output = test_w_h_o.copy()

        self.assertTrue(np.allclose(network.run(inputs), 0.09998924))

suite = unittest.TestLoader().loadTestsFromModule(TestMethods())
unittest.TextTestRunner().run(suite)

.....

[[ 0.37275328]
 [-0.03172939]]
[[ 0.10562014 -0.20185996]
 [ 0.39775194  0.50074398]
 [-0.29887597  0.19962801]]

----------------------------------------------------------------------
Ran 5 tests in 0.012s

OK

<unittest.runner.TextTestResult run=5 errors=0 failures=0>

Training the network

Here you'll set the hyperparameters for the network. The strategy here is to find hyperparameters such that the error on the training set is low, but you're not overfitting to the data. If you train the network too long or have too many hidden nodes, it can become overly specific to the training set and will fail to generalize to the validation set. That is, the loss on the validation set will start increasing as the training set loss drops.

You'll also be using a method know as Stochastic Gradient Descent (SGD) to train the network. The idea is that for each training pass, you grab a random sample of the data instead of using the whole data set. You use many more training passes than with normal gradient descent, but each pass is much faster. This ends up training the network more efficiently. You'll learn more about SGD later.

Choose the number of iterations

This is the number of batches of samples from the training data we'll use to train the network. The more iterations you use, the better the model will fit the data. However, if you use too many iterations, then the model with not generalize well to other data, this is called overfitting. You want to find a number here where the network has a low training loss, and the validation loss is at a minimum. As you start overfitting, you'll see the training loss continue to decrease while the validation loss starts to increase.

Choose the learning rate

This scales the size of weight updates. If this is too big, the weights tend to explode and the network fails to fit the data. A good choice to start at is 0.1. If the network has problems fitting the data, try reducing the learning rate. Note that the lower the learning rate, the smaller the steps are in the weight updates and the longer it takes for the neural network to converge.

Choose the number of hidden nodes

The more hidden nodes you have, the more accurate predictions the model will make. Try a few different numbers and see how it affects the performance. You can look at the losses dictionary for a metric of the network performance. If the number of hidden units is too low, then the model won't have enough space to learn and if it is too high there are too many options for the direction that the learning can take. The trick here is to find the right balance in number of hidden units you choose.

import sys

### Set the hyperparameters here ###
iterations = 15000
learning_rate = 0.2
hidden_nodes = 28
output_nodes = 1

N_i = train_features.shape[1]
network = NeuralNetwork(N_i, hidden_nodes, output_nodes, learning_rate)

losses = {'train':[], 'validation':[]}
for ii in range(iterations):
    if (ii == iterations /4):
        learning_rate = 0.1
    if (ii == iterations /2):
        learning_rate = 0.01
    # Go through a random batch of 128 records from the training data set
    batch = np.random.choice(train_features.index, size=128)
    X, y = train_features.ix[batch].values, train_targets.ix[batch]['cnt']
                             
    network.train(X, y)
    
    # Printing out the training progress
    train_loss = MSE(network.run(train_features).T, train_targets['cnt'].values)
    val_loss = MSE(network.run(val_features).T, val_targets['cnt'].values)
    sys.stdout.write("\rProgress: {:2.1f}".format(100 * ii/float(iterations)) \
                     + "% ... Training loss: " + str(train_loss)[:5] \
                     + " ... Validation loss: " + str(val_loss)[:5])
    sys.stdout.flush()
    
    losses['train'].append(train_loss)
    losses['validation'].append(val_loss)

[[ 0.14975639]
 [-0.05961711]
 [-0.28514678]
 [-0.15688828]
 [-0.11862662]
 [ 0.30004148]
 [-0.02086656]
 [ 0.00910532]
 [-0.12022051]
 [ 0.22230765]
 [-0.11750941]
 [ 0.00987445]
 [-0.1313071 ]
 [-0.10962503]
 [ 0.0379409 ]
 [ 0.22395556]
 [-0.13358627]
 [-0.15891254]
 [-0.19501888]
 [-0.13189959]
 [-0.13275893]
 [ 0.42800931]
 [-0.21060875]
 [-0.22526781]
 [ 0.04854085]
 [ 0.14234755]
 [ 0.22212634]
 [-0.20762829]]
[[-0.00880577 -0.08103242  0.14222522 ..., -0.17333171  0.0518412
  -0.05629008]
 [ 0.04282546  0.04766503  0.11315102 ..., -0.2416727  -0.04200535
   0.12000028]
 [-0.05977513  0.01333852 -0.08578021 ...,  0.062085    0.02191754
   0.18309565]
 ..., 
 [-0.19796967 -0.17045249 -0.10032228 ...,  0.11129807 -0.04782549
   0.00178046]
 [-0.26525539 -0.22417535 -0.07275076 ..., -0.11010338  0.03298202
  -0.25204269]
 [ 0.06718382 -0.03587492 -0.08880534 ...,  0.04004497  0.1963333
   0.20337125]]
Progress: 0.0% ... Training loss: 1.070 ... Validation loss: 1.626[[ 0.17874284]
 [-0.02970225]
 [-0.2579287 ]
 [-0.13225969]
 [-0.08462983]
 [ 0.33182679]
 [ 0.01368779]
 [ 0.02690306]
 [-0.09741612]
 [ 0.25277393]
 [-0.08826851]
 [ 0.03679932]
 [-0.08972469]
 [-0.08252352]
 [ 0.06570616]
 [ 0.25736215]
 [-0.10411383]
 [-0.13345715]
 [-0.16760222]
 [-0.09850174]
 [-0.09922298]
 [ 0.45530912]
 [-0.18044601]
 [-0.19730855]
 [ 0.08014927]
 [ 0.16761249]
 [ 0.2543386 ]
 [-0.18060525]]
[[-0.00688142 -0.08179919  0.13856002 ..., -0.17156224  0.05462779
  -0.05890822]
 [ 0.04284897  0.04765504  0.11310364 ..., -0.24165147 -0.0419687
   0.11996758]
 [-0.05724521  0.01230233 -0.09063546 ...,  0.06448982  0.02566312
   0.17953978]
 ..., 
 [-0.19818972 -0.17036387 -0.09989742 ...,  0.11108513 -0.04813174
   0.00207848]
 [-0.26486048 -0.22433079 -0.07347457 ..., -0.1097493   0.03355219
  -0.25257533]
 [ 0.0674653  -0.035982   -0.08931484 ...,  0.04030311  0.19676723
   0.20300167]]
Progress: 0.0% ... Training loss: 0.969 ... Validation loss: 1.308[[ 0.17360692]
 [-0.03428127]
 [-0.26055755]
 [-0.14078774]
 [-0.08866283]
 [ 0.33101822]
 [ 0.01527153]
 [ 0.0137437 ]
 [-0.10234001]
 [ 0.25035026]
 [-0.09192236]
 [ 0.03103954]
 [-0.08907839]
 [-0.08835262]
 [ 0.06278231]
 [ 0.25788106]
 [-0.10963201]
 [-0.14042719]
 [-0.16727187]
 [-0.09907832]
 [-0.1029156 ]
 [ 0.44989452]
 [-0.18437002]
 [-0.20438932]
 [ 0.08225204]
 [ 0.16552484]
 [ 0.2498873 ]
 [-0.1822282 ]]
[[-0.00638504 -0.08187917  0.13784145 ..., -0.17111058  0.05537051
  -0.05942197]
 [ 0.04272191  0.04767663  0.11328636 ..., -0.24176897 -0.04214163
   0.12009593]
 [-0.05344698  0.01165602 -0.09619421 ...,  0.06803047  0.0310513
   0.17570122]
 ..., 
 [-0.19772946 -0.17043794 -0.1005355  ...,  0.11151081 -0.04748615
   0.00162048]
 [-0.265163   -0.22428001 -0.07303028 ..., -0.11003252  0.03312632
  -0.25228851]
 [ 0.06761972 -0.0360067  -0.08952004 ...,  0.04043396  0.19700164
   0.20286448]]
Progress: 0.0% ... Training loss: 0.951 ... Validation loss: 1.321[[ 0.15294538]
 [-0.05226527]
 [-0.27435449]
 [-0.16072051]
 [-0.10577235]
 [ 0.31953597]
 [ 0.00280488]
 [-0.01088371]
 [-0.11803019]
 [ 0.23388545]
 [-0.10734344]
 [ 0.01330049]
 [-0.10307468]
 [-0.10439602]
 [ 0.04665039]
 [ 0.24355125]
 [-0.12878019]
 [-0.15468749]
 [-0.1814838 ]
 [-0.11139463]
 [-0.11961978]
 [ 0.43322589]
 [-0.20231716]
 [-0.22469511]
 [ 0.07329208]
 [ 0.147193  ]
 [ 0.23153509]
 [-0.19585015]]
[[-0.00606651 -0.08193629  0.13744159 ..., -0.1708789   0.05583418
  -0.05973986]
 [ 0.04252555  0.04771454  0.11357561 ..., -0.24195062 -0.04240538
   0.12029992]
 [-0.05016089  0.01099367 -0.10120507 ...,  0.07114734  0.03574283
   0.17223634]
 ..., 
 [-0.19791554 -0.17040105 -0.10024727 ...,  0.11132865 -0.04774755
   0.00182336]
 [-0.26495376 -0.22432108 -0.07332442 ..., -0.10985095  0.03342914
  -0.2525085 ]
 [ 0.06735069 -0.03594837 -0.08908493 ...,  0.04016605  0.19663308
   0.20313225]]
Progress: 0.0% ... Training loss: 0.973 ... Validation loss: 1.472[[ 0.17284093]
 [-0.03431648]
 [-0.25405736]
 [-0.15032866]
 [-0.08686491]
 [ 0.33953909]
 [ 0.02761362]
 [-0.00215152]
 [-0.09997677]
 [ 0.26028434]
 [-0.0859314 ]
 [ 0.03197332]
 [-0.0762503 ]
 [-0.08696836]
 [ 0.0670145 ]
 [ 0.26833866]
 [-0.10980432]
 [-0.13798687]
 [-0.15957291]
 [-0.08973043]
 [-0.09815845]
 [ 0.45303695]
 [-0.18143306]
 [-0.20990982]
 [ 0.09767606]
 [ 0.16623349]
 [ 0.25532277]
 [-0.17800064]]
[[-0.00424236 -0.08255571  0.13416555 ..., -0.16913108  0.0584882
  -0.06207053]
 [ 0.04269895  0.04765483  0.11326527 ..., -0.24178441 -0.04214513
   0.12007899]
 [-0.04629351  0.00966468 -0.10813376 ...,  0.07486345  0.04146678
   0.16725074]
 ..., 
 [-0.19691754 -0.17073814 -0.10201358 ...,  0.11229028 -0.04628613
   0.00054107]
 [-0.2644971  -0.22447449 -0.07415619 ..., -0.10941608  0.03408666
  -0.25309152]
 [ 0.06734698 -0.03595005 -0.0891019  ...,  0.04016749  0.19665487
   0.20312798]]
Progress: 0.0% ... Training loss: 0.940 ... Validation loss: 1.289[[ 0.15912554]
 [-0.04791171]
 [-0.26700838]
 [-0.16719374]
 [-0.09944578]
 [ 0.33267991]
 [ 0.0175165 ]
 [-0.02372579]
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[[-0.00377491 -0.08265045  0.13350355 ..., -0.16869074  0.05922894
  -0.06255757]
 [ 0.04269895  0.04765483  0.11326527 ..., -0.24178441 -0.04214513
   0.12007899]
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  -0.25253326]
 [ 0.06758876 -0.03599674 -0.08943767 ...,  0.04041779  0.19701745
   0.2028636 ]]
Progress: 0.0% ... Training loss: 0.926 ... Validation loss: 1.379[[ 0.16728107]
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[[ -1.52876975e-03  -8.33223788e-02   1.29798552e-01 ...,  -1.66608449e-01
    6.26080406e-02  -6.51720857e-02]
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   -4.25169535e-02   1.20379880e-01]
 [ -3.96339416e-02   7.94634582e-03  -1.18701132e-01 ...,   8.11507139e-02
    5.13356129e-02   1.59841734e-01]
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 [ -1.96684417e-01  -1.70858941e-01  -1.02472651e-01 ...,   1.12494829e-01
   -4.59339307e-02   1.84832618e-04]
 [ -2.65128302e-01  -2.24343992e-01  -7.32266733e-02 ...,  -1.10013439e-01
    3.31877130e-02  -2.52465014e-01]
 [  6.75375205e-02  -3.59762769e-02  -8.93149638e-02 ...,   4.03551449e-02
    1.96932594e-01   2.02934833e-01]]
Progress: 0.0% ... Training loss: 0.915 ... Validation loss: 1.292[[ 0.14596717]
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[[-0.00149671 -0.08332928  0.12976833 ..., -0.16655607  0.06270498
  -0.06521189]
 [ 0.04250556  0.04771724  0.11359353 ..., -0.2419553  -0.04241369
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  -0.25200419]
 [ 0.06731597 -0.03592207 -0.08896315 ...,  0.04014102  0.1966285
   0.20317486]]
Progress: 0.0% ... Training loss: 0.935 ... Validation loss: 1.455[[ 0.1632306 ]
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[[ -2.00517909e-04  -8.38340431e-02   1.27436802e-01 ...,  -1.65335239e-01
    6.46982320e-02  -6.68936420e-02]
 [  4.24992511e-02   4.77197100e-02   1.13605331e-01 ...,  -2.41956583e-01
   -4.24226031e-02   1.20324128e-01]
 [ -3.45426527e-02   6.27678265e-03  -1.27465212e-01 ...,   8.60691983e-02
    5.92397555e-02   1.53630126e-01]
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 [ -1.97234527e-01  -1.70726003e-01  -1.01616735e-01 ...,   1.11977538e-01
   -4.67429892e-02   7.56847661e-04]
 [ -2.65303623e-01  -2.24347961e-01  -7.30503378e-02 ...,  -1.10153893e-01
    3.29959431e-02  -2.52383944e-01]
 [  6.74930066e-02  -3.59879616e-02  -8.92708174e-02 ...,   4.02955636e-02
    1.96908731e-01   2.02955462e-01]]
Progress: 0.1% ... Training loss: 0.901 ... Validation loss: 1.281[[ 0.14864151]
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[[ 0.00037068 -0.08397067  0.12659084 ..., -0.16482733  0.06556903
  -0.06752528]
 [ 0.04258507  0.04769765  0.11345824 ..., -0.24187805 -0.0422786
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 [-0.19706612 -0.1707659  -0.10188102 ...,  0.11211797 -0.04651344
   0.00055732]
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  -0.2522861 ]
 [ 0.06721196 -0.0359163  -0.08879357 ...,  0.04000679  0.19647763
   0.20327637]]
Progress: 0.1% ... Training loss: 0.895 ... Validation loss: 1.380[[ 0.15480598]
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[[  1.12492071e-03  -8.42566269e-02   1.25249999e-01 ...,  -1.64048530e-01
    6.68104675e-02  -6.85176685e-02]
 [  4.24687332e-02   4.77395563e-02   1.13665568e-01 ...,  -2.41999659e-01
   -4.24643060e-02   1.20353679e-01]
 [ -2.95608530e-02   4.79071088e-03  -1.35752419e-01 ...,   9.09732124e-02
    6.69604530e-02   1.47659838e-01]
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 [ -1.96826429e-01  -1.70852372e-01  -1.02284200e-01 ...,   1.12351065e-01
   -4.61347566e-02   2.46236924e-04]
 [ -2.65389313e-01  -2.24325597e-01  -7.29049741e-02 ...,  -1.10244205e-01
    3.28867818e-02  -2.52270691e-01]
 [  6.73527402e-02  -3.59692862e-02  -8.90381251e-02 ...,   4.01445326e-02
    1.96708836e-01   2.03083256e-01]]
Progress: 0.1% ... Training loss: 0.878 ... Validation loss: 1.321[[ 0.14791798]
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[[  1.17710665e-03  -8.42670903e-02   1.25186388e-01 ...,  -1.64011681e-01
    6.69455675e-02  -6.85526607e-02]
 [  4.24195396e-02   4.77552317e-02   1.13746950e-01 ...,  -2.42047040e-01
   -4.25411753e-02   1.20413689e-01]
 [ -2.70890838e-02   3.97860143e-03  -1.40063274e-01 ...,   9.34883761e-02
    7.09565606e-02   1.44549789e-01]
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 [ -1.96644322e-01  -1.70907715e-01  -1.02596043e-01 ...,   1.12533830e-01
   -4.58383291e-02   2.56701742e-05]
 [ -2.65398916e-01  -2.24321646e-01  -7.28879028e-02 ...,  -1.10242069e-01
    3.28746362e-02  -2.52271947e-01]
 [  6.69310230e-02  -3.58288442e-02  -8.82752031e-02 ...,   3.97101040e-02
    1.96070409e-01   2.03616254e-01]]
Progress: 0.1% ... Training loss: 0.877 ... Validation loss: 1.359[[ 0.15783019]
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[[  2.24812534e-03  -8.46678565e-02   1.23261082e-01 ...,  -1.62918308e-01
    6.85562881e-02  -6.99387263e-02]
 [  4.24679824e-02   4.77365096e-02   1.13658938e-01 ...,  -2.41996350e-01
   -4.24623687e-02   1.20354153e-01]
 [ -2.48209238e-02   3.11235755e-03  -1.44217311e-01 ...,   9.58643934e-02
    7.44635194e-02   1.41555810e-01]
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 [ -1.96823959e-01  -1.70840627e-01  -1.02271535e-01 ...,   1.12350351e-01
   -4.61300143e-02   2.57274564e-04]
 [ -2.65525275e-01  -2.24272151e-01  -7.26532517e-02 ...,  -1.10381551e-01
    3.26873135e-02  -2.52091997e-01]
 [  6.69483971e-02  -3.58386169e-02  -8.83171738e-02 ...,   3.97274334e-02
    1.96121284e-01   2.03576692e-01]]
Progress: 0.1% ... Training loss: 0.863 ... Validation loss: 1.274[[ 0.16609298]
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[[  3.49854983e-03  -8.50453137e-02   1.21168219e-01 ...,  -1.61665205e-01
    7.04320446e-02  -7.14847395e-02]
 [  4.26527487e-02   4.76805421e-02   1.13351065e-01 ...,  -2.41813873e-01
   -4.21753030e-02   1.20129690e-01]
 [ -2.21040463e-02   2.29069853e-03  -1.48781280e-01 ...,   9.86436360e-02
    7.86422861e-02   1.38271316e-01]
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 [ -1.96694234e-01  -1.70879012e-01  -1.02483946e-01 ...,   1.12491931e-01
   -4.59245948e-02   9.22371346e-05]
 [ -2.65783198e-01  -2.24196715e-01  -7.22331707e-02 ...,  -1.10637409e-01
    3.22928120e-02  -2.51806884e-01]
 [  6.71229342e-02  -3.58908977e-02  -8.85933953e-02 ...,   3.99131009e-02
    1.96391566e-01   2.03343639e-01]]
Progress: 0.1% ... Training loss: 0.874 ... Validation loss: 1.229[[ 0.1442725 ]
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[[ 0.00377087 -0.08510414  0.12077646 ..., -0.16139965  0.07073733
  -0.07176132]
 [ 0.04261282  0.04768927  0.11341683 ..., -0.24185489 -0.0422419
   0.12017203]
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   0.13495772]
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 [-0.19710515 -0.17078426 -0.10186522 ...,  0.11210717 -0.04653931
   0.0005256 ]
 [-0.26576027 -0.22420147 -0.07228805 ..., -0.11060839  0.0323202
  -0.25181168]
 [ 0.066999   -0.03585631 -0.08832801 ...,  0.03976014  0.19616222
   0.20350839]]
Progress: 0.1% ... Training loss: 0.855 ... Validation loss: 1.365[[ 0.16399871]
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[[  5.00636088e-03  -8.55992749e-02   1.18471569e-01 ...,  -1.60136911e-01
    7.27299858e-02  -7.34354508e-02]
 [  4.25673548e-02   4.77074425e-02   1.13502603e-01 ...,  -2.41901734e-01
   -4.23148768e-02   1.20234917e-01]
 [ -1.71259022e-02   7.62723588e-04  -1.57172776e-01 ...,   1.03778739e-01
    8.65210762e-02   1.32112693e-01]
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 [ -1.96717616e-01  -1.70935948e-01  -1.02584502e-01 ...,   1.12496174e-01
   -4.59543691e-02  -1.25262723e-05]
 [ -2.65573619e-01  -2.24276813e-01  -7.26340234e-02 ...,  -1.10417158e-01
    3.26135521e-02  -2.52067987e-01]
 [  6.68035229e-02  -3.57759847e-02  -8.79519233e-02 ...,   3.95506868e-02
    1.95865779e-01   2.03786918e-01]]
Progress: 0.1% ... Training loss: 0.862 ... Validation loss: 1.216[[ 0.14366222]
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[[  5.17245022e-03  -8.56291224e-02   1.18282821e-01 ...,  -1.60022475e-01
    7.29498046e-02  -7.35816468e-02]
 [  4.24712703e-02   4.77307984e-02   1.13657122e-01 ...,  -2.41997632e-01
   -4.24751833e-02   1.20333939e-01]
 [ -1.47993523e-02   2.01563854e-04  -1.60959545e-01 ...,   1.06203798e-01
    9.04986920e-02   1.29514804e-01]
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 [ -1.96782108e-01  -1.70919929e-01  -1.02473538e-01 ...,   1.12430548e-01
   -4.60675397e-02   5.93667640e-05]
 [ -2.66118384e-01  -2.24148739e-01  -7.17910956e-02 ...,  -1.10971170e-01
    3.17826777e-02  -2.51458521e-01]
 [  6.66391616e-02  -3.57353340e-02  -8.76817594e-02 ...,   3.93554169e-02
    1.95638616e-01   2.03993076e-01]]
Progress: 0.1% ... Training loss: 0.839 ... Validation loss: 1.349[[ 0.16096424]
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[[  6.54461583e-03  -8.61920654e-02   1.15722935e-01 ...,  -1.58588946e-01
    7.53065059e-02  -7.55824424e-02]
 [  4.25907850e-02   4.76795611e-02   1.13418698e-01 ...,  -2.41867857e-01
   -4.22615156e-02   1.20157708e-01]
 [ -1.28637258e-02  -6.11509385e-04  -1.64687982e-01 ...,   1.08287561e-01
    9.37883720e-02   1.26717259e-01]
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 [ -1.96858743e-01  -1.70889204e-01  -1.02321334e-01 ...,   1.12349262e-01
   -4.61894985e-02   1.68524611e-04]
 [ -2.66195975e-01  -2.24116353e-01  -7.16390645e-02 ...,  -1.11060194e-01
    3.16500515e-02  -2.51351179e-01]
 [  6.74341118e-02  -3.60643133e-02  -8.91593372e-02 ...,   4.01913291e-02
    1.96976436e-01   2.02844305e-01]]
Progress: 0.1% ... Training loss: 0.837 ... Validation loss: 1.218[[ 0.14706231]
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[[  6.75415840e-03  -8.62414516e-02   1.15382216e-01 ...,  -1.58404417e-01
    7.56695035e-02  -7.58314712e-02]
 [  4.26740074e-02   4.76572919e-02   1.13287431e-01 ...,  -2.41782682e-01
   -4.21270591e-02   1.20068282e-01]
 [ -1.15491939e-02  -9.69397255e-04  -1.66858522e-01 ...,   1.09650751e-01
    9.60171062e-02   1.25144214e-01]
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 [ -1.96896412e-01  -1.70876157e-01  -1.02254657e-01 ...,   1.12318061e-01
   -4.62747922e-02   2.15024210e-04]
 [ -2.66828213e-01  -2.23946749e-01  -7.06065570e-02 ...,  -1.11696361e-01
    3.06401366e-02  -2.50614346e-01]
 [  6.70290422e-02  -3.59547398e-02  -8.84883645e-02 ...,   3.97783298e-02
    1.96314349e-01   2.03327995e-01]]
Progress: 0.1% ... Training loss: 0.825 ... Validation loss: 1.334[[ 0.15628956]
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[[  8.21342149e-03  -8.68069236e-02   1.12715366e-01 ...,  -1.56987851e-01
    7.80576962e-02  -7.78478190e-02]
 [  4.25488939e-02   4.77085029e-02   1.13530929e-01 ...,  -2.41907200e-01
   -4.23312822e-02   1.20249821e-01]
 [ -9.34017432e-03  -1.86009441e-03  -1.70968993e-01 ...,   1.11928807e-01
    9.96067213e-02   1.22029070e-01]
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 [ -1.96833530e-01  -1.70899575e-01  -1.02375688e-01 ...,   1.12382519e-01
   -4.61586323e-02   1.09491479e-04]
 [ -2.66851985e-01  -2.23936774e-01  -7.05567116e-02 ...,  -1.11711589e-01
    3.06059192e-02  -2.50573260e-01]
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    1.96996461e-01   2.02779840e-01]]
Progress: 0.1% ... Training loss: 0.813 ... Validation loss: 1.242[[ 0.14507016]
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[[  8.48306488e-03  -8.68903758e-02   1.12321573e-01 ...,  -1.56710425e-01
    7.84667614e-02  -7.81927762e-02]
 [  4.24280696e-02   4.77455400e-02   1.13737369e-01 ...,  -2.42025779e-01
   -4.25213516e-02   1.20397987e-01]
 [ -6.66028295e-03  -2.68750688e-03  -1.75578432e-01 ...,   1.14648437e-01
    1.04094444e-01   1.18724786e-01]
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 [ -1.96741323e-01  -1.70925346e-01  -1.02509083e-01 ...,   1.12476747e-01
   -4.60414464e-02  -1.27552985e-05]
 [ -2.66705543e-01  -2.23979231e-01  -7.08177484e-02 ...,  -1.11562421e-01
    3.08508826e-02  -2.50729438e-01]
 [  6.72903723e-02  -3.60746730e-02  -8.89845253e-02 ...,   4.00466565e-02
    1.96819262e-01   2.02953683e-01]]
Progress: 0.1% ... Training loss: 0.811 ... Validation loss: 1.338[[ 0.14266993]
 [-0.06658034]
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[[  9.10087528e-03  -8.71570039e-02   1.11163872e-01 ...,  -1.56060697e-01
    7.96091464e-02  -7.90101575e-02]
 [  4.24284930e-02   4.77449820e-02   1.13734334e-01 ...,  -2.42021757e-01
   -4.25174522e-02   1.20398968e-01]
 [ -5.46560732e-03  -3.20480715e-03  -1.77898987e-01 ...,   1.15897922e-01
    1.06256517e-01   1.17022469e-01]
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 [ -1.96889573e-01  -1.70862057e-01  -1.02214180e-01 ...,   1.12332926e-01
   -4.62813370e-02   2.00039266e-04]
 [ -2.66730223e-01  -2.23964661e-01  -7.07626447e-02 ...,  -1.11588265e-01
    3.08358696e-02  -2.50641748e-01]
 [  6.72882315e-02  -3.60768052e-02  -8.89801711e-02 ...,   4.00506989e-02
    1.96823648e-01   2.02947253e-01]]
Progress: 0.1% ... Training loss: 0.814 ... Validation loss: 1.365[[ 0.15407552]
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[[  1.03084024e-02  -8.77273253e-02   1.08785423e-01 ...,  -1.54814352e-01
    8.17227194e-02  -8.08012745e-02]
 [  4.25433179e-02   4.76881555e-02   1.13502820e-01 ...,  -2.41893724e-01
   -4.22895271e-02   1.20216379e-01]
 [ -3.73735654e-03  -4.01732519e-03  -1.81311645e-01 ...,   1.17706858e-01
    1.09258556e-01   1.14442935e-01]
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 [ -1.96770477e-01  -1.70915313e-01  -1.02446803e-01 ...,   1.12462449e-01
   -4.60809695e-02   1.20384148e-05]
 [ -2.66904222e-01  -2.23883039e-01  -7.04185492e-02 ...,  -1.11766952e-01
    3.05562524e-02  -2.50377595e-01]
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    1.96677985e-01   2.03032112e-01]]
Progress: 0.1% ... Training loss: 0.792 ... Validation loss: 1.261[[ 0.15945367]
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[[  1.12051192e-02  -8.80907374e-02   1.07110905e-01 ...,  -1.53857813e-01
    8.32734764e-02  -8.20280080e-02]
 [  4.26371034e-02   4.76520273e-02   1.13334317e-01 ...,  -2.41798083e-01
   -4.21302563e-02   1.20099597e-01]
 [ -1.62239447e-03  -4.86493287e-03  -1.85145614e-01 ...,   1.19816787e-01
    1.12845423e-01   1.11587907e-01]
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 [ -1.96632747e-01  -1.70965967e-01  -1.02673291e-01 ...,   1.12595388e-01
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 [ -2.67156466e-01  -2.23787712e-01  -6.99581681e-02 ...,  -1.12024652e-01
    3.01238667e-02  -2.50055992e-01]
 [  6.73328223e-02  -3.60878039e-02  -8.90074289e-02 ...,   4.00917304e-02
    1.96856961e-01   2.02899406e-01]]
Progress: 0.2% ... Training loss: 0.786 ... Validation loss: 1.223[[ 0.1574218 ]
 [-0.05920339]
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[[  1.23095403e-02  -8.84700676e-02   1.05291861e-01 ...,  -1.52789935e-01
    8.50407067e-02  -8.34074668e-02]
 [  4.24817772e-02   4.77062179e-02   1.13603781e-01 ...,  -2.41949565e-01
   -4.23934279e-02   1.20289408e-01]
 [  4.76748604e-05  -5.43364157e-03  -1.87917462e-01 ...,   1.21436636e-01
    1.15561925e-01   1.09483401e-01]
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 [ -1.96338438e-01  -1.71066791e-01  -1.03160801e-01 ...,   1.12870341e-01
   -4.53550310e-02  -5.23551850e-04]
 [ -2.67239292e-01  -2.23757271e-01  -6.97722797e-02 ...,  -1.12099422e-01
    2.99802684e-02  -2.49945021e-01]
 [  6.71721347e-02  -3.60320712e-02  -8.86989555e-02 ...,   3.99408027e-02
    1.96596104e-01   2.03116528e-01]]
Progress: 0.2% ... Training loss: 0.778 ... Validation loss: 1.230[[ 0.13896977]
 [-0.07545803]
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[[ 0.01212436 -0.08838801  0.10565855 ..., -0.15298516  0.08473541
  -0.08313467]
 [ 0.04243533  0.04772157  0.11368042 ..., -0.24199283 -0.04246703
   0.12032925]
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   0.10713908]
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 [-0.19643136 -0.17103102 -0.10299671 ...,  0.11278781 -0.04551203
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 [-0.26776601 -0.22356012 -0.06884068 ..., -0.11259174  0.02911183
  -0.24928511]
 [ 0.06694626 -0.03594182 -0.08828107 ...,  0.03970574  0.19621962
   0.20340358]]
Progress: 0.2% ... Training loss: 0.811 ... Validation loss: 1.422[[ 0.17989156]
 [-0.04004218]
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[[ 0.01442038 -0.08965101  0.10083338 ..., -0.15065294  0.08874663
  -0.08684728]
 [ 0.04248571  0.04769419  0.11358436 ..., -0.24194438 -0.04237839
   0.12025078]
 [ 0.00427684 -0.00749492 -0.19637624 ...,  0.12570172  0.12276517
   0.10309488]
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 [-0.19616546 -0.17117058 -0.10355082 ...,  0.11306339 -0.04503467
  -0.00085997]
 [-0.26736816 -0.22377502 -0.06968054 ..., -0.11219648  0.02978512
  -0.24988017]
 [ 0.06737795 -0.03618783 -0.08920237 ...,  0.0401499   0.19699036
   0.20268398]]
Progress: 0.2% ... Training loss: 0.858 ... Validation loss: 1.127[[ 0.13466414]
 [-0.08369801]
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[[ 0.01351187 -0.08944459  0.10224235 ..., -0.15151513  0.08731136
  -0.08591086]
 [ 0.04239369  0.04771363  0.11370908 ..., -0.2420257  -0.04250996
   0.12034169]
 [ 0.00630678 -0.00795209 -0.19946386 ...,  0.12764719  0.12618602
   0.10098272]
 ..., 
 [-0.19652592 -0.17108989 -0.10298525 ...,  0.11272545 -0.04561665
  -0.00048383]
 [-0.26774624 -0.22369169 -0.06912315 ..., -0.11255859  0.02918433
  -0.24950075]
 [ 0.06674096 -0.03604262 -0.08824153 ...,  0.03953731  0.1959676
   0.20336692]]
Progress: 0.2% ... Training loss: 0.832 ... Validation loss: 1.504[[ 0.15994977]
 [-0.06050148]
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[[ 0.01484959 -0.09028859  0.09921749 ..., -0.15024222  0.08984885
  -0.08817386]
 [ 0.04237124  0.04772747  0.11375844 ..., -0.2420446  -0.04254726
   0.12038543]
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   0.09943979]
 ..., 
 [-0.19610327 -0.17133934 -0.10390073 ...,  0.11312039 -0.0448442
  -0.0011942 ]
 [-0.2678931  -0.22360016 -0.06879749 ..., -0.11269789  0.02894294
  -0.24925226]
 [ 0.06693567 -0.03616949 -0.08865922 ...,  0.03972765  0.19632689
   0.20301287]]
Progress: 0.2% ... Training loss: 0.754 ... Validation loss: 1.211[[ 0.1581049 ]
 [-0.06364826]
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[[ 0.01525523 -0.09045341  0.09848149 ..., -0.14987134  0.0905612
  -0.08876279]
 [ 0.04239639  0.04771775  0.11371317 ..., -0.24202061 -0.04251531
   0.12035054]
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   0.09743113]
 ..., 
 [-0.19618613 -0.17130617 -0.10373419 ...,  0.11305172 -0.04498956
  -0.00109373]
 [-0.26781624 -0.22362878 -0.06894342 ..., -0.11263848  0.02903617
  -0.24938526]
 [ 0.06692547 -0.03616575 -0.08863947 ...,  0.03973557  0.19633967
   0.20301558]]
Progress: 0.2% ... Training loss: 0.749 ... Validation loss: 1.230[[ 0.14379328]
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[[ 0.0158503  -0.09068804  0.09742734 ..., -0.14932031  0.09156378
  -0.0894806 ]
 [ 0.0423998   0.047716    0.11370736 ..., -0.24201452 -0.04250905
   0.12034373]
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   0.09575706]
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Progress: 0.2% ... Training loss: 0.769 ... Validation loss: 1.367[[ 0.15281204]
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Progress: 0.2% ... Training loss: 0.740 ... Validation loss: 1.254[[ 0.16138109]
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   0.20233645]]
Progress: 0.2% ... Training loss: 0.736 ... Validation loss: 1.178[[ 0.15566477]
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 [ 0.06757658 -0.03647163 -0.089846   ...,  0.04037265  0.1974558
   0.20205866]]
Progress: 0.2% ... Training loss: 0.728 ... Validation loss: 1.209[[ 0.16302234]
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   0.20174024]]
Progress: 0.2% ... Training loss: 0.733 ... Validation loss: 1.147[[ 0.16209134]
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[[ 0.0204147  -0.09273593  0.08914425 ..., -0.14496631  0.09948281
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   0.20157522]]
Progress: 0.2% ... Training loss: 0.724 ... Validation loss: 1.150[[ 0.14743433]
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Progress: 0.2% ... Training loss: 0.721 ... Validation loss: 1.282[[ 0.16189782]
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Progress: 0.2% ... Training loss: 0.721 ... Validation loss: 1.134[[ 0.16119843]
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[[ 0.02282374 -0.09386627  0.0845291  ..., -0.14270326  0.10360993
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Progress: 0.3% ... Training loss: 0.718 ... Validation loss: 1.125[[ 0.14855212]
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[[ 0.02284577 -0.0938791   0.08460454 ..., -0.14267545  0.10370077
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Progress: 0.3% ... Training loss: 0.703 ... Validation loss: 1.234[[ 0.15464951]
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   0.20165186]]
Progress: 0.3% ... Training loss: 0.698 ... Validation loss: 1.162[[ 0.14111749]
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[[ 0.0240835  -0.09458068  0.08211302 ..., -0.14153373  0.10597176
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 [ 0.06768532 -0.0364813  -0.08995026 ...,  0.04044392  0.19767     0.20196778]]
Progress: 0.3% ... Training loss: 0.712 ... Validation loss: 1.299[[ 0.14068527]
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[[ 0.02407019 -0.09457627  0.08218274 ..., -0.14157225  0.10597991
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   0.20219265]]
Progress: 0.3% ... Training loss: 0.708 ... Validation loss: 1.294[[ 0.16404833]
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[[ 0.02566767 -0.09563825  0.07863462 ..., -0.13996195  0.10911252
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   0.20188307]]
Progress: 0.3% ... Training loss: 0.720 ... Validation loss: 1.081[[ 0.14261787]
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[[ 0.02553364 -0.09556013  0.07901565 ..., -0.14009594  0.10876874
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   0.20191149]]
Progress: 0.3% ... Training loss: 0.690 ... Validation loss: 1.243[[ 0.1448475 ]
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[[ 0.02570468 -0.09566398  0.0787584  ..., -0.13994794  0.10900871
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   0.20165106]]
Progress: 0.3% ... Training loss: 0.683 ... Validation loss: 1.209[[ 0.15074859]
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[[ 0.02668658 -0.09626266  0.07659854 ..., -0.13897     0.11100893
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 [ 0.06777314 -0.03655123 -0.09005108 ...,  0.04053671  0.19786254
   0.20178278]]
Progress: 0.3% ... Training loss: 0.678 ... Validation loss: 1.155[[ 0.14602546]
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[[ 0.02676021 -0.09628538  0.07654869 ..., -0.1389211   0.11112495
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 [ 0.0674471  -0.03635792 -0.08933063 ...,  0.04022624  0.19720872
   0.20230169]]
Progress: 0.3% ... Training loss: 0.676 ... Validation loss: 1.193[[ 0.14752927]
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[[ 0.02700522 -0.09643706  0.0760569  ..., -0.13866028  0.11169766
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   0.20222516]]
Progress: 0.3% ... Training loss: 0.673 ... Validation loss: 1.182[[ 0.16172938]
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[[ 0.02790356 -0.09699287  0.07401849 ..., -0.13774812  0.11348581
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   0.20209653]]
Progress: 0.3% ... Training loss: 0.689 ... Validation loss: 1.073[[ 0.1366485 ]
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[[ 0.02762113 -0.09684913  0.07460588 ..., -0.13804992  0.11297559
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 [ 0.06752514 -0.03640566 -0.08942603 ...,  0.04030253  0.19740022
   0.20220715]]
Progress: 0.3% ... Training loss: 0.689 ... Validation loss: 1.291[[ 0.1649023 ]
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 [ 0.06767694 -0.03651847 -0.08978518 ...,  0.04045789  0.19769988
   0.20191214]]
Progress: 0.3% ... Training loss: 0.712 ... Validation loss: 1.040[[ 0.1510508 ]
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[[ 0.02918729 -0.09793924  0.07094771 ..., -0.1365451   0.11634074
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   0.20153534]]
Progress: 0.3% ... Training loss: 0.662 ... Validation loss: 1.128[[ 0.13852964]
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[[ 0.02910855 -0.09789471  0.07122608 ..., -0.13661123  0.11621555
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   0.20169882]]
Progress: 0.4% ... Training loss: 0.675 ... Validation loss: 1.261[[ 0.14913297]
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[[ 0.02989438 -0.09849518  0.0693051  ..., -0.1358135   0.11778159
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   0.20149041]]
Progress: 0.4% ... Training loss: 0.657 ... Validation loss: 1.135[[ 0.16200043]
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[[ 0.0313666  -0.09940132  0.06623424 ..., -0.13443253  0.12060609
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   0.2011479 ]]
Progress: 0.4% ... Training loss: 0.686 ... Validation loss: 1.036[[ 0.13905752]
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[[ 0.03114966 -0.09928413  0.06668429 ..., -0.13461884  0.12023592
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   0.20166254]]
Progress: 0.4% ... Training loss: 0.662 ... Validation loss: 1.233[[ 0.14437967]
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[[ 0.03129784 -0.0994034   0.06629731 ..., -0.13446937  0.12056186
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 [ 0.06787402 -0.03667613 -0.09013064 ...,  0.0406583   0.19816921
   0.20152836]]
Progress: 0.4% ... Training loss: 0.650 ... Validation loss: 1.170[[ 0.15018052]
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[[ 0.03198629 -0.09990469  0.06468151 ..., -0.13383674  0.12204746
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 [ 0.06772798 -0.03656621 -0.0897485  ...,  0.04049937  0.19785883
   0.20180754]]
Progress: 0.4% ... Training loss: 0.648 ... Validation loss: 1.111[[ 0.13803263]
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[[ 0.03208755 -0.09995907  0.06452795 ..., -0.13373849  0.12218755
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   0.20238091]]
Progress: 0.4% ... Training loss: 0.659 ... Validation loss: 1.237[[ 0.13706538]
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[[ 0.03221962 -0.1000599   0.06419752 ..., -0.13364492  0.12242631
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   0.20260033]]
Progress: 0.4% ... Training loss: 0.660 ... Validation loss: 1.243[[ 0.15538306]
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[[ 0.033222   -0.10084205  0.06162381 ..., -0.13266915  0.12460335
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   0.20250364]]
Progress: 0.4% ... Training loss: 0.662 ... Validation loss: 1.048[[ 0.12242434]
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[[ 0.03330269 -0.10086743  0.06158196 ..., -0.13261773  0.12468867
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   0.20314867]]
Progress: 0.4% ... Training loss: 0.719 ... Validation loss: 1.414[[ 0.14493621]
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[[ 0.03409979 -0.10167743  0.05922759 ..., -0.13182284  0.12662227
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   0.20270947]]
Progress: 0.4% ... Training loss: 0.642 ... Validation loss: 1.121[[ 0.14458615]
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[[ 0.03435003 -0.10186609  0.05865671 ..., -0.13158153  0.1271372
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   0.20263584]]
Progress: 0.4% ... Training loss: 0.641 ... Validation loss: 1.136[[ 0.14801063]
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[[ 0.03491149 -0.10228223  0.05732227 ..., -0.13106804  0.12833713
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 [ 0.06718553 -0.03626859 -0.08847236 ...,  0.0399395   0.19695512
   0.20268243]]
Progress: 0.4% ... Training loss: 0.639 ... Validation loss: 1.106[[ 0.14412383]
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[[ 0.03497152 -0.10232165  0.05729045 ..., -0.13102273  0.12848005
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   0.20301974]]
Progress: 0.4% ... Training loss: 0.638 ... Validation loss: 1.138[[ 0.13385888]
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[[ 0.03500837 -0.10235094  0.05726464 ..., -0.13100124  0.1285191
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 [ 0.0667057  -0.03592635 -0.08727208 ...,  0.03950734  0.19592933
   0.20363612]]
Progress: 0.4% ... Training loss: 0.658 ... Validation loss: 1.242[[ 0.15786181]
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[[ 0.03626938 -0.10340056  0.05394977 ..., -0.12990379  0.13118935
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   0.20334995]]
Progress: 0.5% ... Training loss: 0.663 ... Validation loss: 1.013[[ 0.11930463]
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[[ 0.03503412 -0.10270288  0.05663214 ..., -0.13094576  0.12870952
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 [ 0.06630626 -0.0357247  -0.08638873 ...,  0.03919324  0.1951335
   0.20425985]]
Progress: 0.5% ... Training loss: 0.732 ... Validation loss: 1.440[[ 0.15221782]
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[[ 0.03589849 -0.10360214  0.05399953 ..., -0.13020779  0.13077575
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   0.20380755]]
Progress: 0.5% ... Training loss: 0.647 ... Validation loss: 1.031[[ 0.15008127]
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[[ 0.03651721 -0.103989    0.05272756 ..., -0.12965512  0.13207751
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 [ 0.06633944 -0.03580843 -0.08654556 ...,  0.03922076  0.19532092
   0.2040679 ]]
Progress: 0.5% ... Training loss: 0.640 ... Validation loss: 1.037[[ 0.14601634]
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[[ 0.03730771 -0.10450199  0.05102878 ..., -0.12895759  0.13365119
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   0.2036989 ]]
Progress: 0.5% ... Training loss: 0.631 ... Validation loss: 1.061[[ 0.14308353]
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[[ 0.03716447 -0.10440292  0.05146224 ..., -0.12908397  0.13318277
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   0.2039333 ]]
Progress: 0.5% ... Training loss: 0.628 ... Validation loss: 1.084[[  1.37633110e-01]
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[[ 0.03747085 -0.1046272   0.05079674 ..., -0.12882415  0.13386139
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   0.20339804]]
Progress: 0.5% ... Training loss: 0.631 ... Validation loss: 1.138[[ 0.14504396]
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[[ 0.03822079 -0.10521819  0.04894717 ..., -0.12819898  0.13544761
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   0.20326443]]
Progress: 0.5% ... Training loss: 0.625 ... Validation loss: 1.071[[ 0.14328218]
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[[ 0.03844653 -0.10536949  0.0484833  ..., -0.12802522  0.13581037
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 [ 0.06681291 -0.03614073 -0.08747474 ...,  0.03962188  0.19634753
   0.20311536]]
Progress: 0.5% ... Training loss: 0.623 ... Validation loss: 1.080[[ 0.14946595]
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[[ 0.03902892 -0.1058016   0.04707735 ..., -0.12754818  0.13727709
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 [ 0.06688537 -0.03619748 -0.08762784 ...,  0.03968147  0.19653269
   0.20296385]]
Progress: 0.5% ... Training loss: 0.627 ... Validation loss: 1.034[[ 0.13366697]
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[[ 0.03908585 -0.10584154  0.04705028 ..., -0.12750681  0.13730231
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   0.20293641]]
Progress: 0.5% ... Training loss: 0.638 ... Validation loss: 1.192[[ 0.15923484]
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[[ 0.04036834 -0.10695609  0.04354112 ..., -0.12646254  0.1401479
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   0.20269548]]
Progress: 0.5% ... Training loss: 0.651 ... Validation loss: 0.982[[ 0.13395757]
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[[ 0.04034647 -0.10695197  0.04361744 ..., -0.12648718  0.14013575
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   0.20313321]]
Progress: 0.5% ... Training loss: 0.639 ... Validation loss: 1.196[[ 0.14873383]
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[[ 0.04101191 -0.10757764  0.04178488 ..., -0.12596173  0.14164557
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   0.20236652]]
Progress: 0.5% ... Training loss: 0.617 ... Validation loss: 1.054[[ 0.12750917]
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[[ 0.04047574 -0.10719175  0.0432355  ..., -0.12636171  0.14033698
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 [ 0.06697818 -0.03637503 -0.08791406 ...,  0.03974953  0.19676969
   0.2025886 ]]
Progress: 0.5% ... Training loss: 0.676 ... Validation loss: 1.298[[ 0.16485982]
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[[ 0.04183817 -0.10852341  0.03928264 ..., -0.12541276  0.14365535
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   0.20253074]]
Progress: 0.6% ... Training loss: 0.680 ... Validation loss: 0.955[[ 0.14527503]
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[[ 0.04159979 -0.1083959   0.03985147 ..., -0.12555894  0.14318284
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 [ 0.06693295 -0.03636058 -0.08777686 ...,  0.03970959  0.19671997
   0.20267126]]
Progress: 0.6% ... Training loss: 0.612 ... Validation loss: 1.057[[ 0.14681834]
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[[ 0.04203443 -0.10873135  0.03879867 ..., -0.12524295  0.14409019
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 [ 0.06711976 -0.03649969 -0.08818014 ...,  0.03983972  0.19708687
   0.20229883]]
Progress: 0.6% ... Training loss: 0.611 ... Validation loss: 1.051[[ 0.1388419 ]
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[[ 0.04208121 -0.10875982  0.03876377 ..., -0.12519372  0.14418634
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 [ 0.06704583 -0.03644767 -0.08798769 ...,  0.03978841  0.19691213
   0.20243256]]
Progress: 0.6% ... Training loss: 0.617 ... Validation loss: 1.121[[ 0.14891863]
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[[ 0.04235565 -0.10899209  0.03808411 ..., -0.12499692  0.14486172
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 [ 0.06724085 -0.03660776 -0.08853167 ...,  0.03992847  0.19739939
   0.20199953]]
Progress: 0.6% ... Training loss: 0.611 ... Validation loss: 1.022[[ 0.12984028]
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[[ 0.04214092 -0.10883389  0.03880797 ..., -0.12513258  0.14425574
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   0.20254217]]
Progress: 0.6% ... Training loss: 0.642 ... Validation loss: 1.207[[ 0.14771529]
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   0.20222443]]
Progress: 0.6% ... Training loss: 0.607 ... Validation loss: 1.023[[ 0.14290314]
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[[ 0.04263412 -0.10932142  0.03725114 ..., -0.124766    0.14551529
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 [ 0.06699098 -0.03646291 -0.08795598 ...,  0.03975131  0.1969542
   0.2024396 ]]
Progress: 0.6% ... Training loss: 0.607 ... Validation loss: 1.076[[ 0.14066432]
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[[ 0.04239803 -0.10914939  0.03793031 ..., -0.12491157  0.14502761
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 [ 0.06694937 -0.0364352  -0.08778598 ...,  0.03974454  0.19684959
   0.20248747]]
Progress: 0.6% ... Training loss: 0.611 ... Validation loss: 1.098[[ 0.15373357]
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[[ 0.04305257 -0.10965836  0.03628673 ..., -0.12450394  0.14648551
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 [ 0.0666752  -0.03620609 -0.08700234 ...,  0.03955386  0.19629412
   0.20311866]]
Progress: 0.6% ... Training loss: 0.613 ... Validation loss: 0.984[[ 0.14872757]
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[[ 0.04330676 -0.10981954  0.03574806 ..., -0.12433402  0.14707645
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   0.20294022]]
Progress: 0.6% ... Training loss: 0.602 ... Validation loss: 1.022[[ 0.14251741]
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[[ 0.04317668 -0.10974936  0.03604659 ..., -0.12438955  0.14691545
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 [ 0.06717118 -0.03655938 -0.08826157 ...,  0.03989346  0.19737354
   0.20209586]]
Progress: 0.6% ... Training loss: 0.605 ... Validation loss: 1.077[[ 0.14479785]
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[[ 0.04358115 -0.11005884  0.03501729 ..., -0.12417209  0.14780469
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 [ 0.06697076 -0.03639713 -0.0876899  ...,  0.03977075  0.19692106
   0.20255007]]
Progress: 0.6% ... Training loss: 0.599 ... Validation loss: 1.037[[ 0.14891501]
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[[ 0.04375253 -0.11020051  0.03455609 ..., -0.1240616   0.14810681
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 [ 0.06706217 -0.03647102 -0.08793317 ...,  0.03982521  0.19712468
   0.20234835]]
Progress: 0.6% ... Training loss: 0.599 ... Validation loss: 1.001[[ 0.14499114]
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[[ 0.04426201 -0.11055271  0.03340131 ..., -0.12374467  0.14939802
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 [ 0.06690902 -0.03635295 -0.08749655 ...,  0.03972679  0.19687125
   0.20268492]]
Progress: 0.6% ... Training loss: 0.596 ... Validation loss: 1.027[[ 0.15864384]
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[[ 0.04539979 -0.11144657  0.03035627 ..., -0.12306862  0.15207532
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 [ 0.06708613 -0.0364918  -0.08795307 ...,  0.03982835  0.19722932
   0.20228938]]
Progress: 0.7% ... Training loss: 0.623 ... Validation loss: 0.941[[ 0.14563187]
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[[ 0.04524585 -0.11135424  0.03076063 ..., -0.12316526  0.15184036
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 [ 0.06721014 -0.0365731  -0.08822216 ...,  0.03990633  0.19751757
   0.20204477]]
Progress: 0.7% ... Training loss: 0.593 ... Validation loss: 1.014[[ 0.14366384]
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[[ 0.04503938 -0.11117536  0.0313955  ..., -0.12329901  0.15134351
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 [ 0.04129787  0.0482808   0.11611157 ..., -0.24288367 -0.04484198
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 [ 0.06741188 -0.03671682 -0.08864593 ...,  0.04001504  0.19796497
   0.20164593]]
Progress: 0.7% ... Training loss: 0.593 ... Validation loss: 1.028[[ 0.1488594 ]
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[[ 0.04542115 -0.11147838  0.03041396 ..., -0.12306929  0.15223054
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 [ 0.06752676 -0.03682156 -0.0889085  ...,  0.0400917   0.19826094
   0.20134131]]
Progress: 0.7% ... Training loss: 0.593 ... Validation loss: 0.987[[ 0.15001262]
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[[ 0.04550413 -0.11152371  0.03040771 ..., -0.12302065  0.15239665
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 [ 0.0413368   0.04825174  0.11603273 ..., -0.2428643  -0.04476403
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 [-0.19581159 -0.1721956  -0.10518453 ...,  0.11348939 -0.04473985
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 [ 0.06767945 -0.03693973 -0.08922783 ...,  0.0401839   0.19866793
   0.20100083]]
Progress: 0.7% ... Training loss: 0.594 ... Validation loss: 0.973[[ 0.13304238]
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[[ 0.04479496 -0.11101564  0.03237116 ..., -0.12342857  0.15066875
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 [ 0.04130364  0.04827157  0.1161167  ..., -0.2428806  -0.04482506
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 [ 0.06768206 -0.03693942 -0.08920608 ...,  0.04018122  0.19866419
   0.20100161]]
Progress: 0.7% ... Training loss: 0.614 ... Validation loss: 1.130[[ 0.14750373]
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[[ 0.04513196 -0.11132932  0.03135547 ..., -0.12325988  0.15146937
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 [ 0.06775789 -0.03700303 -0.08940443 ...,  0.0402171   0.19881871
   0.20084046]]
Progress: 0.7% ... Training loss: 0.589 ... Validation loss: 0.983[[ 0.14496424]
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[[ 0.04553288 -0.11162591  0.03026644 ..., -0.12302496  0.15235422
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 [ 0.04129881  0.04826666  0.11612629 ..., -0.24288475 -0.04484555
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 [ 0.06789478 -0.03711738 -0.08979655 ...,  0.04029527  0.19914102
   0.20052138]]
Progress: 0.7% ... Training loss: 0.586 ... Validation loss: 0.998[[ 0.16253608]
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[[ 0.046617   -0.11249333  0.02729432 ..., -0.12240674  0.15523881
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 [ 0.04128404  0.04827785  0.11616798 ..., -0.24289282 -0.044872    0.1223456 ]
 [ 0.04307274 -0.02848987 -0.27381492 ...,  0.16274687  0.19650761
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 [ 0.06812631 -0.0373079  -0.09045031 ...,  0.04043783  0.19973456
   0.19996875]]
Progress: 0.7% ... Training loss: 0.634 ... Validation loss: 0.916[[ 0.1322603 ]
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[[ 0.04568147 -0.11192735  0.02953778 ..., -0.12295251  0.15303369
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 [ 0.06762517 -0.0369908  -0.08917942 ...,  0.04013394  0.19857058
   0.20096907]]
Progress: 0.7% ... Training loss: 0.615 ... Validation loss: 1.132[[ 0.14309162]
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[[ 0.04600332 -0.11222985  0.0286299  ..., -0.12279101  0.15384738
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 [ 0.04128605  0.04827093  0.1161546  ..., -0.24289373 -0.04486373
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 [ 0.06769614 -0.03705957 -0.08940696 ...,  0.0401701   0.19874665
   0.20078263]]
Progress: 0.7% ... Training loss: 0.584 ... Validation loss: 1.010[[ 0.15357652]
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[[ 0.04622456 -0.11241931  0.02800113 ..., -0.12268091  0.15448439
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 [ 0.04128605  0.04827093  0.1161546  ..., -0.24289373 -0.04486373
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 [ 0.06782037 -0.03716604 -0.08975512 ...,  0.04023732  0.19908958
   0.20047237]]
Progress: 0.7% ... Training loss: 0.590 ... Validation loss: 0.950[[ 0.1350977 ]
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[[  4.57742900e-02  -1.12107256e-01   2.92101155e-02 ...,  -1.22895880e-01
    1.53392495e-01  -1.45645379e-01]
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    1.91320376e-01   4.86885442e-02]
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    2.50409425e-02  -2.46826976e-01]
 [  6.75254707e-02  -3.69582107e-02  -8.89554810e-02 ...,   4.00851637e-02
    1.98424488e-01   2.01099598e-01]]
Progress: 0.7% ... Training loss: 0.608 ... Validation loss: 1.112[[ 0.17694264]
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[[ 0.0472266  -0.11350053  0.02475732 ..., -0.12226987  0.15719413
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 [ 0.0412483   0.0482826   0.11621751 ..., -0.24291539 -0.04493466
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 [ 0.06781709 -0.03724658 -0.08987411 ...,  0.0402228   0.1991558
   0.20030483]]
Progress: 0.7% ... Training loss: 0.701 ... Validation loss: 0.911[[ 0.1219886 ]
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[[  4.49537205e-02  -1.12322856e-01   2.98788590e-02 ...,  -1.23503190e-01
    1.52285342e-01  -1.45305616e-01]
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   -4.50366433e-02   1.22442449e-01]
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    1.90477635e-01   4.92353681e-02]
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 [ -1.97570037e-01  -1.71119074e-01  -1.01077029e-01 ...,   1.12545669e-01
   -4.87408269e-02   1.58562573e-04]
 [ -2.69905017e-01  -2.23144253e-01  -6.52478556e-02 ...,  -1.14151179e-01
    2.43048533e-02  -2.46550609e-01]
 [  6.73045412e-02  -3.69780953e-02  -8.87169440e-02 ...,   3.99414668e-02
    1.98102751e-01   2.01253233e-01]]
Progress: 0.7% ... Training loss: 0.712 ... Validation loss: 1.329[[ 0.15544142]
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[[ 0.04546618 -0.11291512  0.02819351 ..., -0.12332492  0.15361648
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 [-0.19740881 -0.17130386 -0.10161795 ...,  0.11260085 -0.04831366
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 [ 0.0676946  -0.03742833 -0.09009156 ...,  0.04007945  0.19908291
   0.20009549]]
Progress: 0.8% ... Training loss: 0.582 ... Validation loss: 0.952[[ 0.1417409 ]
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[[ 0.04492442 -0.11252753  0.0296591  ..., -0.12359684  0.15226235
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 [ 0.0411843   0.0482723   0.11626703 ..., -0.24295596 -0.04505877
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 [-0.19740901 -0.17130918 -0.10162702 ...,  0.11260295 -0.04833731
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 [ 0.06751407 -0.03729709 -0.0896072  ...,  0.04000163  0.19866061
   0.20046477]]
Progress: 0.8% ... Training loss: 0.591 ... Validation loss: 1.061[[  1.59861686e-01]
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[[ 0.04583339 -0.11330208  0.02708802 ..., -0.12321986  0.15443651
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 [ 0.04126901  0.04819537  0.11601105 ..., -0.242919   -0.04483502
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 [-0.19726104 -0.17143302 -0.10200305 ...,  0.11266367 -0.04797991
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 [-0.26975277 -0.22336311 -0.06584141 ..., -0.11411692  0.02476599
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 [ 0.06764005 -0.03739193 -0.0898687  ...,  0.0400463   0.19895086
   0.20018942]]
Progress: 0.8% ... Training loss: 0.590 ... Validation loss: 0.926[[ 0.14228665]
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[[ 0.04539835 -0.11300595  0.02822988 ..., -0.12342215  0.15334503
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 [ 0.04120037  0.04824023  0.11618624 ..., -0.24295113 -0.04499732
   0.12234695]
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 [-0.19737446 -0.17135957 -0.10173312 ...,  0.11261733 -0.04824288
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  -0.2466537 ]
 [ 0.06784477 -0.03753827 -0.09034697 ...,  0.04014738  0.19939681
   0.19973507]]
Progress: 0.8% ... Training loss: 0.587 ... Validation loss: 1.048[[ 0.15296858]
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[[ 0.0456206  -0.1132028   0.02762877 ..., -0.1233267   0.15382412
  -0.14729461]
 [ 0.04121357  0.0482288   0.1161515  ..., -0.24294488 -0.04496151
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 [-0.19728267 -0.17144439 -0.10198918 ...,  0.11265597 -0.04804501
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 [ 0.06789994 -0.03757594 -0.09047488 ...,  0.04016663  0.19950289
   0.19961408]]
Progress: 0.8% ... Training loss: 0.575 ... Validation loss: 0.962[[ 0.14990627]
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[[ 0.04618887 -0.11361008  0.02628919 ..., -0.1230945   0.15508724
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 [ 0.04119458  0.04824379  0.11620773 ..., -0.24295284 -0.04501218
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 [ 0.06808315 -0.03771868 -0.09096361 ...,  0.0402473   0.19992389
   0.19920618]]
Progress: 0.8% ... Training loss: 0.572 ... Validation loss: 0.977[[ 0.14346515]
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[[ 0.04621741 -0.11363008  0.02623501 ..., -0.12309895  0.15514492
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 [ 0.0411234   0.04830187  0.11641722 ..., -0.24298092 -0.04519172
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 [ 0.06787407 -0.03755343 -0.09036545 ...,  0.04016902  0.19942574
   0.19968984]]
Progress: 0.8% ... Training loss: 0.580 ... Validation loss: 1.028[[ 0.15364456]
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[[ 0.04671751 -0.11407152  0.02492884 ..., -0.12289781  0.1563284
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 [ 0.06780951 -0.03749923 -0.09020548 ...,  0.04014433  0.19934678
   0.19985332]]
Progress: 0.8% ... Training loss: 0.572 ... Validation loss: 0.951[[ 0.16058688]
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[[ 0.04716766 -0.11440395  0.02397033 ..., -0.12269834  0.15707994
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 [ 0.04108965  0.04833598  0.11656785 ..., -0.24299064 -0.04530136
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  -0.24643277]
 [ 0.06809498 -0.03772347 -0.09092633 ...,  0.04026982  0.19996836
   0.19918597]]
Progress: 0.8% ... Training loss: 0.585 ... Validation loss: 0.912[[ 0.14565105]
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[[ 0.04717105 -0.11441027  0.02401915 ..., -0.12272744  0.15685137
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 [ 0.04096333  0.04842164  0.1168926  ..., -0.24304377 -0.0455978
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 [ 0.06816562 -0.03776997 -0.09109116 ...,  0.04030377  0.2001498
   0.19903072]]
Progress: 0.8% ... Training loss: 0.572 ... Validation loss: 0.998[[ 0.14881272]
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[[ 0.0474624  -0.11464387  0.02335254 ..., -0.12263031  0.15741001
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 [ 0.04103849  0.04835784  0.11667981 ..., -0.24301675 -0.04544657
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 [ 0.0680739  -0.03768692 -0.09079437 ...,  0.04026696  0.19990673
   0.19925947]]
Progress: 0.8% ... Training loss: 0.567 ... Validation loss: 0.965[[ 0.15413262]
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[[ 0.04742129 -0.11462895  0.02350776 ..., -0.12263539  0.15727231
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 [ 0.06795052 -0.03758725 -0.09044266 ...,  0.04022576  0.1996241
   0.19955611]]
Progress: 0.8% ... Training loss: 0.568 ... Validation loss: 0.939[[  1.56306547e-01]
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[[ 0.047732   -0.11488457  0.02280257 ..., -0.12251802  0.15792656
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 [ 0.04094128  0.04842871  0.11694296 ..., -0.24304965 -0.04566856
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 [-0.19699229 -0.17171091 -0.10298009 ...,  0.11275238 -0.04747424
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  -0.24676342]
 [ 0.06796444 -0.03760094 -0.09045617 ...,  0.04023099  0.19970298
   0.1994961 ]]
Progress: 0.8% ... Training loss: 0.568 ... Validation loss: 0.929[[ 0.14491683]
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[[ 0.04760084 -0.11479234  0.02314742 ..., -0.1225528   0.15756735
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 [ 0.04085104  0.04849511  0.11718367 ..., -0.24308039 -0.04589034
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 [-0.19717489 -0.17157406 -0.10250951 ...,  0.11269382 -0.04798033
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  -0.24623402]
 [ 0.06783741 -0.03750242 -0.09009467 ...,  0.04018595  0.19941806
   0.19980513]]
Progress: 0.8% ... Training loss: 0.572 ... Validation loss: 1.009[[ 0.14989129]
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[[ 0.04788501 -0.11504543  0.02244109 ..., -0.12246082  0.15829149
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 [ 0.04085742  0.04848943  0.11716426 ..., -0.24307857 -0.04587309
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 [-0.1971884  -0.17156135 -0.10247458 ...,  0.11268907 -0.04799431
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  -0.24615057]
 [ 0.06812782 -0.03775552 -0.09095178 ...,  0.04028066  0.20015496
   0.19910515]]
Progress: 0.8% ... Training loss: 0.563 ... Validation loss: 0.964[[ 0.16417244]
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[[ 0.04884225 -0.11582984  0.01978886 ..., -0.12215437  0.16053807
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 [ 0.04093658  0.04842505  0.1169538  ..., -0.2430534  -0.04568253
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 [-0.1969764  -0.17173608 -0.10307523 ...,  0.11276079 -0.04750379
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  -0.24671563]
 [ 0.0683768  -0.03796751 -0.0916454  ...,  0.04037003  0.20073142
   0.19848786]]
Progress: 0.9% ... Training loss: 0.586 ... Validation loss: 0.892[[ 0.14411572]
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[[ 0.04848019 -0.11556657  0.02077754 ..., -0.12229497  0.15955895
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 [ 0.04101813  0.04836933  0.11674553 ..., -0.24302357 -0.04550327
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 ..., 
 [-0.19725146 -0.17155073 -0.10237788 ...,  0.11266259 -0.04819939
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  -0.24710848]
 [ 0.06795529 -0.03766641 -0.09051663 ...,  0.04020744  0.19975848
   0.19940125]]
Progress: 0.9% ... Training loss: 0.569 ... Validation loss: 1.002[[ 0.16580211]
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[[ 0.04958992 -0.11657753  0.01761572 ..., -0.1219662   0.16227315
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 [ 0.04104598  0.04834342  0.11666083 ..., -0.24301502 -0.04542563
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 [-0.19694105 -0.17183333 -0.10328732 ...,  0.1127549  -0.04755653
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 [-0.26944145 -0.22359397 -0.06651076 ..., -0.11404256  0.02525936
  -0.24754865]
 [ 0.06820417 -0.03789676 -0.0912289  ...,  0.04027977  0.20040668
   0.19877768]]
Progress: 0.9% ... Training loss: 0.591 ... Validation loss: 0.885[[ 0.15032762]
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[[ 0.04937682 -0.11644309  0.01822767 ..., -0.12203488  0.16170962
  -0.1561626 ]
 [ 0.0408811   0.04845579  0.11705518 ..., -0.24307346 -0.04582477
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 [-0.19707049 -0.17174042 -0.10294224 ...,  0.11270559 -0.04781384
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 [ 0.06830673 -0.03796624 -0.09143211 ...,  0.0403143   0.20064744
   0.1985838 ]]
Progress: 0.9% ... Training loss: 0.559 ... Validation loss: 0.957[[  1.46678577e-01]
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[[ 0.04901991 -0.11612807  0.01936082 ..., -0.1221337   0.16077227
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   0.1992057 ]]
Progress: 0.9% ... Training loss: 0.561 ... Validation loss: 0.978[[  1.46536501e-01]
 [ -1.28870772e-01]
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[[ 0.04895248 -0.11607477  0.01961686 ..., -0.12215309  0.16060018
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 [ 0.06806627 -0.03776114 -0.09057905 ...,  0.04024964  0.2001424
   0.19915694]]
Progress: 0.9% ... Training loss: 0.563 ... Validation loss: 0.985[[ 0.15547113]
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[[ 0.04947057 -0.11654491  0.01818266 ..., -0.12203482  0.1619009
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 [ 0.04084597  0.04848627  0.11716253 ..., -0.24308208 -0.04592203
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   0.19896888]]
Progress: 0.9% ... Training loss: 0.556 ... Validation loss: 0.922[[ 0.1461856 ]
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[[ 0.04928019 -0.11639949  0.018795   ..., -0.1220769   0.16154536
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 [ 0.06793739 -0.03766316 -0.09022654 ...,  0.04021638  0.19991657
   0.19943765]]
Progress: 0.9% ... Training loss: 0.561 ... Validation loss: 0.982[[ 0.16038501]
 [-0.11584243]
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[[ 0.04996135 -0.11699061  0.01690095 ..., -0.12193198  0.16323829
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 [ 0.06807714 -0.0377862  -0.09059479 ...,  0.04024628  0.20023422
   0.1991077 ]]
Progress: 0.9% ... Training loss: 0.563 ... Validation loss: 0.894[[ 0.15248487]
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[[ 0.04995929 -0.11697422  0.01714018 ..., -0.12193039  0.16320479
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   0.19949657]]
Progress: 0.9% ... Training loss: 0.552 ... Validation loss: 0.926[[ 0.15173856]
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   0.19996664]]
Progress: 0.9% ... Training loss: 0.550 ... Validation loss: 0.930[[ 0.15764797]
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 [ 0.06759243 -0.03739603 -0.08916194 ...,  0.0401223   0.19903124
   0.20025371]]
Progress: 0.9% ... Training loss: 0.554 ... Validation loss: 0.897[[ 0.16672013]
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[[ 0.05128434 -0.11801452  0.01375977 ..., -0.12160453  0.16636833
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   0.20046128]]
Progress: 0.9% ... Training loss: 0.580 ... Validation loss: 0.871[[ 0.14597904]
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[[ 0.05110558 -0.1178869   0.01429166 ..., -0.12166407  0.16578734
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 [ 0.06720907 -0.03713349 -0.08813041 ...,  0.04002127  0.19810005
   0.20113041]]
Progress: 0.9% ... Training loss: 0.554 ... Validation loss: 0.972[[ 0.14273868]
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[[ 0.05087777 -0.11769114  0.0150528  ..., -0.12170573  0.16514964
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 [ 0.06712256 -0.03705527 -0.08784986 ...,  0.04000572  0.19787737
   0.20135126]]
Progress: 0.9% ... Training loss: 0.562 ... Validation loss: 0.996[[ 0.15331669]
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[[ 0.05104723 -0.11786394  0.01457776 ..., -0.12167256  0.16554894
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 [ 0.06720071 -0.03712455 -0.08805887 ...,  0.0400191   0.198096
   0.20114315]]
Progress: 1.0% ... Training loss: 0.545 ... Validation loss: 0.916[[ 0.15125934]
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[[ 0.05106178 -0.11788162  0.01452244 ..., -0.1216733   0.16560308
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 [ 0.06709745 -0.03704258 -0.08772103 ...,  0.03999872  0.19787519
   0.20138661]]
Progress: 1.0% ... Training loss: 0.545 ... Validation loss: 0.930[[ 0.15254529]
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[[ 0.05147644 -0.11820666  0.01346282 ..., -0.12159912  0.16643372
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 [-0.19587537 -0.17267977 -0.1061857  ...,  0.1129935  -0.04502724
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 [ 0.0670169  -0.0369801  -0.08743452 ...,  0.03998455  0.19772541
   0.20159262]]
Progress: 1.0% ... Training loss: 0.542 ... Validation loss: 0.921[[ 0.164635  ]
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[[ 0.05212442 -0.1187531   0.01169917 ..., -0.12148241  0.16810861
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 [ 0.06704786 -0.03700848 -0.08752942 ...,  0.03999072  0.19786255
   0.20149146]]
Progress: 1.0% ... Training loss: 0.560 ... Validation loss: 0.867[[  1.41233946e-01]
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[[ 0.05141353 -0.11827037  0.0135663  ..., -0.12164695  0.16633702
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 [ 0.04047643  0.04876279  0.11818673 ..., -0.24316084 -0.04689268
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  -0.24617408]
 [ 0.06720224 -0.03711559 -0.0878939  ...,  0.04002784  0.19816504
   0.20112641]]
Progress: 1.0% ... Training loss: 0.565 ... Validation loss: 1.002[[ 0.16537809]
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[[ 0.05221343 -0.11905138  0.01109822 ..., -0.1215472   0.16849038
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 [ 0.06753826 -0.03743982 -0.08893201 ...,  0.04007021  0.19900468
   0.20016695]]
Progress: 1.0% ... Training loss: 0.558 ... Validation loss: 0.862[[ 0.14087123]
 [-0.13735913]
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 [ 0.65533643]
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[[ 0.05130226 -0.11840663  0.01362634 ..., -0.12177669  0.16625754
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 [-0.19594799 -0.17269272 -0.10606174 ...,  0.1129466  -0.04516564
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  -0.24499032]
 [ 0.06725218 -0.03724473 -0.08814512 ...,  0.03999945  0.19830476
   0.20082782]]
Progress: 1.0% ... Training loss: 0.570 ... Validation loss: 1.008[[ 0.15550711]
 [-0.12288068]
 [-0.45297591]
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 [ 0.67021242]
 [ 0.22619602]
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[[ 0.0515853  -0.11867794  0.0128896  ..., -0.12173878  0.16699697
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  -0.24558583]
 [ 0.06742044 -0.03741729 -0.0887127  ...,  0.04001993  0.19885266
   0.20038031]]
Progress: 1.0% ... Training loss: 0.537 ... Validation loss: 0.892[[ 0.1479822 ]
 [-0.13084088]
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[[ 0.0515106  -0.11862039  0.01320305 ..., -0.12175836  0.16665223
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 [ 0.06753856 -0.03752321 -0.08902155 ...,  0.04004069  0.19915321
   0.20004587]]
Progress: 1.0% ... Training loss: 0.542 ... Validation loss: 0.937[[ 0.16185388]
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[[ 0.0519297  -0.11901001  0.01200293 ..., -0.12168864  0.16776578
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 [ 0.06761518 -0.03759284 -0.08925795 ...,  0.0400539   0.19933233
   0.19981769]]
Progress: 1.0% ... Training loss: 0.542 ... Validation loss: 0.865[[ 0.16221022]
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[[ 0.05288866 -0.11972549  0.0095025  ..., -0.12149232  0.17008319
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   0.19988744]]
Progress: 1.0% ... Training loss: 0.541 ... Validation loss: 0.859[[ 0.15687605]
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[[ 0.05294305 -0.11976954  0.00932545 ..., -0.12147704  0.17021613
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 [ 0.06769789 -0.03766064 -0.08941065 ...,  0.04007418  0.19956536
   0.19962544]]
Progress: 1.0% ... Training loss: 0.532 ... Validation loss: 0.881[[ 0.15904308]
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[[ 0.05319021 -0.11999896  0.00857966 ..., -0.12142653  0.17079411
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 [ 0.06787674 -0.03781526 -0.08992766 ...,  0.04010834  0.20007352
   0.19915088]]
Progress: 1.0% ... Training loss: 0.533 ... Validation loss: 0.870[[ 0.15702685]
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[[ 0.05336327 -0.12012433  0.00812775 ..., -0.12139072  0.17108731
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 [-0.19586254 -0.17280885 -0.1063016  ...,  0.11294254 -0.04512061
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 [ 0.06800585 -0.03792068 -0.09024431 ...,  0.04013304  0.20035166
   0.19879787]]
Progress: 1.0% ... Training loss: 0.530 ... Validation loss: 0.874[[ 0.16603854]
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[[ 0.05337783 -0.12016586  0.00826192 ..., -0.12137723  0.17110846
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 [-0.19561697 -0.1730131  -0.10698612 ...,  0.11298678 -0.04446515
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 [ 0.06784227 -0.03777641 -0.08974552 ...,  0.04010285  0.19992086
   0.19921301]]
Progress: 1.0% ... Training loss: 0.540 ... Validation loss: 0.845[[ 0.15767578]
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[[ 0.05340908 -0.12019831  0.00824121 ..., -0.12137591  0.17101994
  -0.1662826 ]
 [ 0.04031514  0.04887009  0.11860988 ..., -0.24319601 -0.04730551
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 [ 0.06764733 -0.03761824 -0.08916365 ...,  0.04006014  0.19943778
   0.19967179]]
Progress: 1.1% ... Training loss: 0.528 ... Validation loss: 0.884[[ 0.15397395]
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[[ 0.05315963 -0.11997361  0.00900207 ..., -0.1214126   0.17038534
  -0.16566087]
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 [-0.19549667 -0.17311369 -0.10734224 ...,  0.11300354 -0.04413875
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 [ 0.06778572 -0.03774576 -0.08956659 ...,  0.04008495  0.19981649
   0.19933553]]
Progress: 1.1% ... Training loss: 0.530 ... Validation loss: 0.908[[ 0.1656616 ]
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[[ 0.05340656 -0.12021883  0.00839029 ..., -0.12137496  0.17110094
  -0.16630231]
 [ 0.04037298  0.04881607  0.11846792 ..., -0.243185   -0.04712318
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 [-0.19524551 -0.17334071 -0.10805879 ...,  0.11303615 -0.0435264
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 [ 0.06793518 -0.03788583 -0.08999122 ...,  0.04010408  0.20022655
   0.19894106]]
Progress: 1.1% ... Training loss: 0.533 ... Validation loss: 0.846[[ 0.15198073]
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[[ 0.05298946 -0.11988987  0.00956808 ..., -0.12145686  0.17007008
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   0.19933015]]
Progress: 1.1% ... Training loss: 0.530 ... Validation loss: 0.916[[ 0.15824852]
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[[ 0.05305785 -0.11996574  0.00943045 ..., -0.12144445  0.17021781
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 [ 0.04037494  0.04880136  0.11841473 ..., -0.24318484 -0.04707211
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   0.19869096]]
Progress: 1.1% ... Training loss: 0.523 ... Validation loss: 0.876[[ 0.17003601]
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   0.19842158]]
Progress: 1.1% ... Training loss: 0.540 ... Validation loss: 0.831[[ 0.15365964]
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   0.19902418]]
Progress: 1.1% ... Training loss: 0.529 ... Validation loss: 0.913[[ 0.17480089]
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   0.19887643]]
Progress: 1.1% ... Training loss: 0.550 ... Validation loss: 0.822[[ 0.15760619]
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   0.19843509]]
Progress: 1.1% ... Training loss: 0.521 ... Validation loss: 0.885[[ 0.16388158]
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[[ 0.05383734 -0.120895    0.00742459 ..., -0.12140907  0.17233088
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   0.19870594]]
Progress: 1.1% ... Training loss: 0.518 ... Validation loss: 0.848[[ 0.14994473]
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Progress: 1.1% ... Training loss: 0.532 ... Validation loss: 0.926[[ 0.16850378]
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[[ 0.05366686 -0.12084461  0.00792419 ..., -0.12147038  0.17197615
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   0.19808696]]
Progress: 1.1% ... Training loss: 0.528 ... Validation loss: 0.822[[ 0.15245443]
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[[ 0.0528515  -0.12019438  0.01023176 ..., -0.12158536  0.16989272
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   0.19792343]]
Progress: 1.1% ... Training loss: 0.521 ... Validation loss: 0.896[[ 0.15840095]
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[[ 0.05316983 -0.12050865  0.00923738 ..., -0.12157024  0.17071734
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   0.19721117]]
Progress: 1.1% ... Training loss: 0.512 ... Validation loss: 0.858[[ 0.15823527]
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[[ 0.05271478 -0.12012616  0.01058381 ..., -0.12159867  0.16955023
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   0.19701358]]
Progress: 1.1% ... Training loss: 0.513 ... Validation loss: 0.870[[ 0.17584189]
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[[ 0.05350902 -0.12086888  0.00829501 ..., -0.12156662  0.17148787
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   0.19638036]]
Progress: 1.2% ... Training loss: 0.539 ... Validation loss: 0.813[[  1.57620810e-01]
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[[ 0.05311117 -0.12056104  0.00940078 ..., -0.12161422  0.17043635
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   0.19726888]]
Progress: 1.2% ... Training loss: 0.513 ... Validation loss: 0.872[[ 0.16111667]
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[[ 0.0527584  -0.12023593  0.01065825 ..., -0.12162609  0.16941851
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   0.19677187]]
Progress: 1.2% ... Training loss: 0.508 ... Validation loss: 0.855[[  1.53284568e-01]
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[[ 0.05284213 -0.12029387  0.01047649 ..., -0.121623    0.1696221
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   0.19707893]]
Progress: 1.2% ... Training loss: 0.524 ... Validation loss: 0.906[[ 0.17061774]
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[[ 0.05362939 -0.12107187  0.00817852 ..., -0.12162348  0.17161887
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   0.19644279]]
Progress: 1.2% ... Training loss: 0.513 ... Validation loss: 0.818[[  1.54805838e-01]
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[[ 0.05279031 -0.120402    0.0106328  ..., -0.12168728  0.16951359
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   0.19672805]]
Progress: 1.2% ... Training loss: 0.522 ... Validation loss: 0.902[[ 0.17306226]
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[[ 0.05377177 -0.12138048  0.00758497 ..., -0.12168462  0.17223874
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   0.1964487 ]]
Progress: 1.2% ... Training loss: 0.510 ... Validation loss: 0.811[[ 0.16514151]
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[[ 0.05376295 -0.12139741  0.0075963  ..., -0.12168506  0.17221004
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 [ 0.06870393 -0.03884897 -0.0921672  ...,  0.04008693  0.20277456
   0.19644999]]
Progress: 1.2% ... Training loss: 0.502 ... Validation loss: 0.839[[ 0.16772291]
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[[ 0.0537854  -0.12144658  0.00762958 ..., -0.12168335  0.17226092
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   0.19627091]]
Progress: 1.2% ... Training loss: 0.501 ... Validation loss: 0.829[[  1.65564127e-01]
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[[ 0.05385578 -0.12154054  0.00740856 ..., -0.1216788   0.17240454
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   0.19637157]]
Progress: 1.2% ... Training loss: 0.502 ... Validation loss: 0.844[[  1.64372176e-01]
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   0.19684128]]
Progress: 1.2% ... Training loss: 0.502 ... Validation loss: 0.848[[ 0.15922499]
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[[ 0.05391069 -0.1215649   0.00742819 ..., -0.12167748  0.1724085
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   0.19751413]]
Progress: 1.2% ... Training loss: 0.515 ... Validation loss: 0.885[[ 0.17601219]
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[[ 0.05462486 -0.12226064  0.00525991 ..., -0.12170015  0.1743337
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   0.19648297]]
Progress: 1.2% ... Training loss: 0.505 ... Validation loss: 0.800[[  1.67350426e-01]
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[[ 0.05442653 -0.12210339  0.00590412 ..., -0.12171045  0.17364529
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   0.19653713]]
Progress: 1.2% ... Training loss: 0.497 ... Validation loss: 0.833[[ 0.17305223]
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[[ 0.05471751 -0.12239511  0.00515827 ..., -0.12170546  0.17428158
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   0.19654428]]
Progress: 1.2% ... Training loss: 0.494 ... Validation loss: 0.807[[ 0.17397181]
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[[ 0.05454285 -0.1222345   0.00573394 ..., -0.12171069  0.1738541
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   0.19696782]]
Progress: 1.3% ... Training loss: 0.494 ... Validation loss: 0.803[[ 0.17489696]
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[[ 0.05474313 -0.12242597  0.00528773 ..., -0.12170243  0.17440868
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   0.19628458]]
Progress: 1.3% ... Training loss: 0.492 ... Validation loss: 0.802[[ 0.17278034]
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   0.19661125]]
Progress: 1.3% ... Training loss: 0.490 ... Validation loss: 0.805[[ 0.1645418 ]
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   0.19681751]]
Progress: 1.3% ... Training loss: 0.498 ... Validation loss: 0.845[[ 0.17198596]
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   0.1965488 ]]
Progress: 1.3% ... Training loss: 0.488 ... Validation loss: 0.808[[ 0.18132823]
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   0.19575935]]
Progress: 1.3% ... Training loss: 0.499 ... Validation loss: 0.785[[ 0.16581803]
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   0.19649259]]
Progress: 1.3% ... Training loss: 0.499 ... Validation loss: 0.850[[ 0.16060218]
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   0.1969589 ]]
Progress: 1.3% ... Training loss: 0.519 ... Validation loss: 0.889[[ 0.18712038]
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[[ 0.05580001 -0.12360653  0.00254633 ..., -0.12180368  0.17678029
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   0.19618424]]
Progress: 1.3% ... Training loss: 0.506 ... Validation loss: 0.778[[ 0.15512177]
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[[ 0.05466765 -0.12274041  0.00563868 ..., -0.12186574  0.17400838
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   0.19757107]]
Progress: 1.3% ... Training loss: 0.552 ... Validation loss: 0.939[[  1.77745132e-01]
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[[ 0.0552058  -0.12334882  0.00394403 ..., -0.12193875  0.17540113
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 [ 0.06822133 -0.03864041 -0.09082349 ...,  0.03999192  0.20206338
   0.1971593 ]]
Progress: 1.3% ... Training loss: 0.482 ... Validation loss: 0.790[[ 0.1785069 ]
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[[ 0.05500623 -0.1231733   0.00461749 ..., -0.12193623  0.17474716
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 [ 0.06816564 -0.03859861 -0.09065916 ...,  0.03999263  0.20193384
   0.19728263]]
Progress: 1.3% ... Training loss: 0.481 ... Validation loss: 0.788[[  1.79457462e-01]
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[[ 0.05514535 -0.12326974  0.00438538 ..., -0.12194013  0.17495377
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 [ 0.06814132 -0.03858971 -0.09056223 ...,  0.03999246  0.20188559
   0.19728015]]
Progress: 1.3% ... Training loss: 0.480 ... Validation loss: 0.782[[ 0.17159103]
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[[ 0.05481903 -0.12302807  0.00538509 ..., -0.12193132  0.17408414
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   0.19679367]]
Progress: 1.3% ... Training loss: 0.486 ... Validation loss: 0.818[[ 0.18457401]
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[[ 0.05548057 -0.12361112  0.00342129 ..., -0.12199217  0.17571965
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   0.19612591]]
Progress: 1.3% ... Training loss: 0.484 ... Validation loss: 0.771[[ 0.16550329]
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[[ 0.05495779 -0.1231563   0.00504859 ..., -0.1219758   0.17433393
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   0.19698873]]
Progress: 1.4% ... Training loss: 0.501 ... Validation loss: 0.847[[  1.92853407e-01]
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[[ 0.05583472 -0.12406446  0.00219784 ..., -0.12209842  0.17667002
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  -0.24502303]
 [ 0.06869984 -0.03918778 -0.09239089 ...,  0.03990774  0.2034145
   0.1956016 ]]
Progress: 1.4% ... Training loss: 0.509 ... Validation loss: 0.775[[ 0.17228269]
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 [-0.55924882]
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 [ 0.24782507]
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[[ 0.05479535 -0.12330968  0.00496207 ..., -0.12209979  0.17419132
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 [ 0.06841739 -0.03898175 -0.09161855 ...,  0.03990736  0.20273875
   0.19626944]]
Progress: 1.4% ... Training loss: 0.485 ... Validation loss: 0.815[[ 0.20232762]
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[[ 0.0562431  -0.12469634  0.00065851 ..., -0.12226586  0.1778171
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  -0.2448817 ]
 [ 0.06846025 -0.0390307  -0.09181083 ...,  0.03990215  0.20294016
   0.19615436]]
Progress: 1.4% ... Training loss: 0.547 ... Validation loss: 0.791[[ 0.15837276]
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[[ 0.05457022 -0.12352376  0.00505158 ..., -0.12231497  0.17378782
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 [ 0.06793869 -0.03867431 -0.09043641 ...,  0.03988755  0.20167509
   0.19728758]]
Progress: 1.4% ... Training loss: 0.552 ... Validation loss: 0.923[[ 0.1951188 ]
 [-0.14276436]
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[[ 0.05569412 -0.12482689  0.00113982 ..., -0.12256209  0.17695351
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 [ 0.068255   -0.03904568 -0.09153883 ...,  0.03981676  0.2025913
   0.19629684]]
Progress: 1.4% ... Training loss: 0.507 ... Validation loss: 0.769[[ 0.18730012]
 [-0.15112637]
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[[ 0.0563239  -0.12528174 -0.00032035 ..., -0.12256611  0.17834833
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 [ 0.06796694 -0.03883299 -0.09070242 ...,  0.03981842  0.20189129
   0.19697272]]
Progress: 1.4% ... Training loss: 0.477 ... Validation loss: 0.755[[ 0.1650193 ]
 [-0.17136931]
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[[ 0.05526641 -0.12441553  0.00275393 ..., -0.12252547  0.17570437
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 [ 0.06754718 -0.03847786 -0.08946929 ...,  0.03983241  0.20081047
   0.19797739]]
Progress: 1.4% ... Training loss: 0.502 ... Validation loss: 0.844[[ 0.17481202]
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[[ 0.05552178 -0.12468687  0.0020146  ..., -0.12257023  0.17644202
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   0.19705125]]
Progress: 1.4% ... Training loss: 0.470 ... Validation loss: 0.783[[ 0.194884  ]
 [-0.14422349]
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[[ 0.05666288 -0.12572311 -0.00127006 ..., -0.12269409  0.17897028
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 [ 0.06793016 -0.03887258 -0.09064919 ...,  0.03977241  0.20188838
   0.19686169]]
Progress: 1.4% ... Training loss: 0.505 ... Validation loss: 0.763[[ 0.16605497]
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[[ 0.05526687 -0.12465455  0.00268953 ..., -0.12267805  0.17534037
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 [ 0.06798484 -0.03891255 -0.09077052 ...,  0.03977178  0.20201982
   0.19675027]]
Progress: 1.4% ... Training loss: 0.497 ... Validation loss: 0.831[[ 0.18431243]
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[[ 0.05550624 -0.12488469  0.00208833 ..., -0.12272414  0.17578579
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 [-0.19644076 -0.17299635 -0.10545389 ...,  0.11266508 -0.04693081
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 [ 0.06791536 -0.03884008 -0.09054244 ...,  0.03978386  0.20182849
   0.19698103]]
Progress: 1.4% ... Training loss: 0.465 ... Validation loss: 0.750[[ 0.1801333 ]
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[[ 0.05522201 -0.12463763  0.00298569 ..., -0.12270557  0.17514531
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 [ 0.06807432 -0.03896943 -0.09101814 ...,  0.03977198  0.20238284
   0.19663751]]
Progress: 1.4% ... Training loss: 0.461 ... Validation loss: 0.758[[  1.82616136e-01]
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[[ 0.05526352 -0.12466365  0.00313804 ..., -0.12270837  0.17513599
  -0.17534173]
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 [-0.19612249 -0.17327257 -0.10636963 ...,  0.11263331 -0.04625406
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 [ 0.06826224 -0.03914004 -0.09148479 ...,  0.03975282  0.20290392
   0.19611244]]
Progress: 1.4% ... Training loss: 0.460 ... Validation loss: 0.749[[ 0.17021203]
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[[ 0.05467982 -0.12416009  0.00498047 ..., -0.12266494  0.17357874
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 [ 0.03897213  0.0499241   0.12252109 ..., -0.24322188 -0.05078168
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 [-0.19640606 -0.1730296  -0.1055469  ...,  0.11265468 -0.04700997
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 [ 0.06802715 -0.03893829 -0.09078475 ...,  0.03977006  0.20231588
   0.1966926 ]]
Progress: 1.4% ... Training loss: 0.477 ... Validation loss: 0.797[[ 0.18740351]
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[[ 0.05542378 -0.1249011   0.00272087 ..., -0.12277131  0.1755175
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 [ 0.03914122  0.04975895  0.12196547 ..., -0.24324628 -0.05031214
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Progress: 1.5% ... Training loss: 0.468 ... Validation loss: 0.744[[  1.80117266e-01]
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[[ 0.05531888 -0.1248283   0.00306977 ..., -0.12276917  0.17530511
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Progress: 1.5% ... Training loss: 0.456 ... Validation loss: 0.750[[ 0.18706929]
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[[ 0.05539794 -0.12490475  0.0029184  ..., -0.12277759  0.17547877
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   0.19618938]]
Progress: 1.5% ... Training loss: 0.462 ... Validation loss: 0.742[[ 0.17777303]
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 [ 0.06788086 -0.0388374  -0.09033522 ...,  0.0397734   0.20203123
   0.19702806]]
Progress: 1.5% ... Training loss: 0.457 ... Validation loss: 0.758[[ 0.17714999]
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   0.19600677]]
Progress: 1.5% ... Training loss: 0.456 ... Validation loss: 0.756[[ 0.17507254]
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   0.19612579]]
Progress: 1.5% ... Training loss: 0.461 ... Validation loss: 0.767[[ 0.18708751]
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   0.19577673]]
Progress: 1.5% ... Training loss: 0.454 ... Validation loss: 0.734[[ 0.18035671]
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Progress: 1.5% ... Training loss: 0.452 ... Validation loss: 0.745[[ 0.18925669]
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Progress: 1.5% ... Training loss: 0.452 ... Validation loss: 0.729[[ 0.17456357]
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[[ 0.05533674 -0.12489854  0.00388337 ..., -0.12280036  0.17497433
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   0.19662402]]
Progress: 1.5% ... Training loss: 0.467 ... Validation loss: 0.771[[ 0.19653492]
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[[ 0.0561326  -0.12568684  0.00139185 ..., -0.12294366  0.17692887
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   0.19675226]]
Progress: 1.5% ... Training loss: 0.468 ... Validation loss: 0.732[[ 0.17924047]
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[[ 0.05521756 -0.12497125  0.00408462 ..., -0.12288138  0.17432176
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   0.19693627]]
Progress: 1.5% ... Training loss: 0.451 ... Validation loss: 0.744[[ 0.17814234]
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[[ 0.05520452 -0.12493936  0.00428728 ..., -0.12287777  0.17417216
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   0.1969906 ]]
Progress: 1.5% ... Training loss: 0.452 ... Validation loss: 0.746[[ 0.18823574]
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[[ 0.05580194 -0.12552823  0.00249827 ..., -0.12299868  0.17581351
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   0.19653151]]
Progress: 1.5% ... Training loss: 0.445 ... Validation loss: 0.720[[ 0.18817731]
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[[ 0.05592028 -0.12564332  0.00223837 ..., -0.12301451  0.17616365
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   0.19591057]]
Progress: 1.5% ... Training loss: 0.444 ... Validation loss: 0.720[[  1.83641765e-01]
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[[ 0.05529859 -0.12510897  0.00418663 ..., -0.12292563  0.17439588
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   0.19610574]]
Progress: 1.6% ... Training loss: 0.443 ... Validation loss: 0.730[[ 0.18801242]
 [-0.16434073]
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 [-0.19214512]
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 [ 0.27775121]
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[[ 0.05553966 -0.12534046  0.00352451 ..., -0.12296267  0.17503424
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 [ 0.06814115 -0.03915515 -0.09098587 ...,  0.03971322  0.20301469
   0.1961703 ]]
Progress: 1.6% ... Training loss: 0.440 ... Validation loss: 0.719[[ 0.19194969]
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[[ 0.05589451 -0.12566398  0.00251991 ..., -0.12301855  0.1758809
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 [ 0.03907621  0.04975822  0.12210199 ..., -0.24326884 -0.05046387
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 [ 0.06825024 -0.03923898 -0.09129055 ...,  0.03969753  0.20329111
   0.19587042]]
Progress: 1.6% ... Training loss: 0.441 ... Validation loss: 0.713[[ 0.1966938 ]
 [-0.15798221]
 [-0.57653592]
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[[ 0.05612563 -0.12587516  0.00201176 ..., -0.12305461  0.17623753
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 [ 0.0679207  -0.03895117 -0.0902631  ...,  0.0397463   0.20241185
   0.19669711]]
Progress: 1.6% ... Training loss: 0.446 ... Validation loss: 0.711[[  1.87824222e-01]
 [ -1.66649774e-01]
 [ -5.84609313e-01]
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[[ 0.055887   -0.12568436  0.00282675 ..., -0.12302207  0.17531052
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 [-0.19516716 -0.17416327 -0.1088169  ...,  0.1124399  -0.04442333
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  -0.24179508]
 [ 0.06788034 -0.03891519 -0.09012328 ...,  0.03975264  0.20231263
   0.19678507]]
Progress: 1.6% ... Training loss: 0.438 ... Validation loss: 0.718[[ 0.20353191]
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[[ 0.05673915 -0.12641802  0.00038943 ..., -0.12316154  0.17743558
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 [ 0.06790554 -0.038946   -0.09020429 ...,  0.03974746  0.20241571
   0.19667751]]
Progress: 1.6% ... Training loss: 0.467 ... Validation loss: 0.715[[ 0.17813526]
 [-0.17615703]
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[[ 0.0556201  -0.12555124  0.00357061 ..., -0.12306398  0.17449787
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 [-0.1951974  -0.1741494  -0.10881444 ...,  0.11242218 -0.04458332
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 [-0.27277881 -0.22211981 -0.05826366 ..., -0.11496164  0.01569    -0.24122375]
 [ 0.06763864 -0.03873495 -0.08943295 ...,  0.03977099  0.20180301
   0.19731406]]
Progress: 1.6% ... Training loss: 0.458 ... Validation loss: 0.751[[ 0.20223742]
 [-0.15382201]
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[[ 0.05630732 -0.12623227  0.00141798 ..., -0.12321885  0.1763926
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  -0.2419111 ]
 [ 0.06820825 -0.03931211 -0.0913122  ...,  0.03964181  0.20343127
   0.1956254 ]]
Progress: 1.6% ... Training loss: 0.459 ... Validation loss: 0.711[[ 0.18915128]
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[[ 0.05601452 -0.1260366   0.00224393 ..., -0.12319259  0.17559188
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 [ 0.06791013 -0.03907189 -0.09043524 ...,  0.0396705   0.20266964
   0.1963865 ]]
Progress: 1.6% ... Training loss: 0.434 ... Validation loss: 0.709[[ 0.19639823]
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[[ 0.05616242 -0.12619982  0.00179822 ..., -0.12322208  0.17597305
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  -0.24146946]
 [ 0.06798883 -0.03915507 -0.09070035 ...,  0.03965506  0.20293219
   0.19615835]]
Progress: 1.6% ... Training loss: 0.434 ... Validation loss: 0.697[[ 0.19736468]
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[[ 0.05637699 -0.12641042  0.00116084 ..., -0.12325359  0.1766215
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 [-0.19508518 -0.17422471 -0.10898788 ...,  0.11241976 -0.0443165
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  -0.24131727]
 [ 0.06809652 -0.03926657 -0.09106229 ...,  0.03963599  0.20323546
   0.195746  ]]
Progress: 1.6% ... Training loss: 0.434 ... Validation loss: 0.695[[ 0.19617752]
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[[ 0.05641008 -0.12642323  0.00107506 ..., -0.12325234  0.17673845
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 [-0.19525197 -0.17408585 -0.10850593 ...,  0.11243994 -0.04471787
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   0.19535454]]
Progress: 1.6% ... Training loss: 0.432 ... Validation loss: 0.696[[ 0.19127466]
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[[ 0.05595638 -0.12604595  0.00243141 ..., -0.12319508  0.17560072
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   0.1960805 ]]
Progress: 1.6% ... Training loss: 0.431 ... Validation loss: 0.704[[ 0.20501884]
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[[  5.68436629e-02  -1.26904583e-01  -2.63867716e-04 ...,  -1.23331003e-01
    1.78062295e-01  -1.79667753e-01]
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   -5.13315791e-02   1.28100861e-01]
 [  2.89494854e-02  -1.96153248e-02  -2.29286371e-01 ...,   1.60146335e-01
    1.56360053e-01   7.80307795e-02]
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 [ -1.94874025e-01  -1.74438653e-01  -1.09599550e-01 ...,   1.12378865e-01
   -4.36516208e-02  -9.24754241e-03]
 [ -2.72535188e-01  -2.22402975e-01  -5.91093509e-02 ...,  -1.15045335e-01
    1.62642947e-02  -2.41909601e-01]
 [  6.79164077e-02  -3.91370163e-02  -9.05327801e-02 ...,   3.96548661e-02
    2.02790544e-01   1.96144541e-01]]
Progress: 1.6% ... Training loss: 0.444 ... Validation loss: 0.694[[ 0.18713742]
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   0.1967221 ]]
Progress: 1.6% ... Training loss: 0.437 ... Validation loss: 0.716[[ 0.20527247]
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[[ 0.05778268 -0.12782227 -0.00269587 ..., -0.1235431   0.18017617
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 [ 0.03865736  0.05009607  0.12329528 ..., -0.2432213  -0.05151835
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   0.19588009]]
Progress: 1.7% ... Training loss: 0.440 ... Validation loss: 0.690[[ 0.1812183 ]
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[[ 0.0564182  -0.12668618  0.00131636 ..., -0.1234055   0.17656374
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 [ 0.03864141  0.05010956  0.12334358 ..., -0.24321976 -0.05156064
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  -0.24092151]
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   0.19627645]]
Progress: 1.7% ... Training loss: 0.459 ... Validation loss: 0.746[[ 0.19803667]
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[[ 0.0566819  -0.12696749  0.00045968 ..., -0.12346426  0.17720966
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  -0.2413031 ]
 [ 0.06804281 -0.03935781 -0.09113735 ...,  0.03958264  0.20340655
   0.19555959]]
Progress: 1.7% ... Training loss: 0.426 ... Validation loss: 0.688[[ 0.19659582]
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[[ 0.0567015  -0.1269985   0.00057253 ..., -0.12347175  0.17729083
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  -0.24132019]
 [ 0.06760659 -0.03897538 -0.0897869  ...,  0.03963994  0.20227082
   0.1966771 ]]
Progress: 1.7% ... Training loss: 0.424 ... Validation loss: 0.688[[ 0.1995259 ]
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[[ 0.05628409 -0.12667003  0.00173795 ..., -0.12342033  0.1762933
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   0.19655115]]
Progress: 1.7% ... Training loss: 0.424 ... Validation loss: 0.684[[ 0.20719577]
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[[ 0.05682894 -0.12712838  0.00042109 ..., -0.12348509  0.17745238
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   0.19654542]]
Progress: 1.7% ... Training loss: 0.435 ... Validation loss: 0.681[[ 0.20595019]
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[[  5.69317900e-02  -1.27228483e-01   2.09636290e-04 ...,  -1.23498120e-01
    1.77703652e-01  -1.80106521e-01]
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   -5.15268870e-02   1.28302743e-01]
 [  2.88200470e-02  -1.96552576e-02  -2.28006449e-01 ...,   1.60071105e-01
    1.55584907e-01   7.83421130e-02]
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 [ -2.73299474e-01  -2.21796447e-01  -5.68498849e-02 ...,  -1.14975871e-01
    1.41078394e-02  -2.40011983e-01]
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    2.02792437e-01   1.96173200e-01]]
Progress: 1.7% ... Training loss: 0.428 ... Validation loss: 0.676[[ 0.20601404]
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[[  5.69855476e-02  -1.27285405e-01   1.22595740e-04 ...,  -1.23504059e-01
    1.77524287e-01  -1.80250377e-01]
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    1.53686335e-01   7.97680326e-02]
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 [ -1.94861616e-01  -1.74513952e-01  -1.09551613e-01 ...,   1.12315691e-01
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    1.42217687e-02  -2.40254827e-01]
 [  6.77043611e-02  -3.90838162e-02  -9.01187103e-02 ...,   3.96266934e-02
    2.02664762e-01   1.96392278e-01]]
Progress: 1.7% ... Training loss: 0.425 ... Validation loss: 0.674[[ 0.20603918]
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[[ 0.05729848 -0.12756175 -0.00061719 ..., -0.12354906  0.17801652
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   0.1957672 ]]
Progress: 1.7% ... Training loss: 0.421 ... Validation loss: 0.672[[ 0.19877624]
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[[ 0.05691624 -0.12724345  0.00061233 ..., -0.12348743  0.17688769
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 [ 0.0386687   0.05006896  0.12326434 ..., -0.24322711 -0.05149311
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 [-0.19537478 -0.17409489 -0.10808442 ...,  0.11238584 -0.04542335
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 [ 0.06753562 -0.03893715 -0.08958668 ...,  0.03965315  0.20220112
   0.19679526]]
Progress: 1.7% ... Training loss: 0.419 ... Validation loss: 0.679[[ 0.21440578]
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[[ 0.0572532  -0.12755088 -0.00036122 ..., -0.1235536   0.17775862
  -0.18096445]
 [ 0.03872136  0.05001654  0.12309744 ..., -0.24323864 -0.05133261
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 [-0.19484913 -0.17455722 -0.10971167 ...,  0.11228667 -0.04407789
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 [ 0.06733603 -0.03876572 -0.08901284 ...,  0.03968896  0.20167564
   0.19731566]]
Progress: 1.7% ... Training loss: 0.440 ... Validation loss: 0.680[[ 0.18754498]
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[[ 0.05549522 -0.12619046  0.00460164 ..., -0.12332486  0.17322632
  -0.17680425]
 [ 0.03863427  0.05008     0.12334015 ..., -0.24322802 -0.05154595
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 [-0.19518429 -0.174308   -0.10880086 ...,  0.11232599 -0.0449652
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  -0.23927027]
 [ 0.06658618 -0.03817962 -0.08688001 ...,  0.03978747  0.19985421
   0.19913642]]
Progress: 1.7% ... Training loss: 0.455 ... Validation loss: 0.735[[ 0.21028691]
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[[ 0.0561824  -0.12690958  0.0023327  ..., -0.12351895  0.17513532
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 [ 0.03864072  0.05007339  0.12331271 ..., -0.24322951 -0.05152913
   0.12833649]
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 [-0.19514764 -0.17434512 -0.1089183  ...,  0.11231722 -0.04486159
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 [-0.27314891 -0.22202241 -0.0574437  ..., -0.11505156  0.01441688
  -0.24050519]
 [ 0.06694837 -0.03856018 -0.08807654 ...,  0.03968293  0.20090946
   0.1980348 ]]
Progress: 1.7% ... Training loss: 0.420 ... Validation loss: 0.670[[ 0.21274629]
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[[ 0.05608795 -0.12684701  0.00266959 ..., -0.12350724  0.17489429
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 [ 0.03876156  0.04997312  0.12294734 ..., -0.24325169 -0.05120068
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   0.19842787]]
Progress: 1.7% ... Training loss: 0.423 ... Validation loss: 0.669[[ 0.21458461]
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[[ 0.0563505  -0.12708233  0.00217176 ..., -0.12355865  0.17528542
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   0.19913154]]
Progress: 1.7% ... Training loss: 0.422 ... Validation loss: 0.666[[ 0.205898  ]
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[[ 0.0561575  -0.12694221  0.0027726  ..., -0.12353683  0.17486321
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   0.19998495]]
Progress: 1.8% ... Training loss: 0.412 ... Validation loss: 0.666[[ 0.21004956]
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[[ 0.05623918 -0.12700405  0.00268751 ..., -0.12355382  0.17507546
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   0.20024568]]
Progress: 1.8% ... Training loss: 0.410 ... Validation loss: 0.660[[ 0.20058258]
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[[ 0.05566797 -0.12650906  0.00443213 ..., -0.12345088  0.17361067
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   0.20054297]]
Progress: 1.8% ... Training loss: 0.420 ... Validation loss: 0.682[[ 0.22339867]
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[[  5.71780735e-02  -1.27926731e-01   3.82219168e-06 ...,  -1.23801068e-01
    1.77562658e-01  -1.81574483e-01]
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    1.53164813e-01   7.91848063e-02]
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 [ -2.73838663e-01  -2.21478453e-01  -5.53732314e-02 ...,  -1.14946939e-01
    1.26140665e-02  -2.38742878e-01]
 [  6.60699856e-02  -3.78441952e-02  -8.55657721e-02 ...,   3.98282291e-02
    1.99010784e-01   2.00205511e-01]]
Progress: 1.8% ... Training loss: 0.444 ... Validation loss: 0.677[[ 0.19931366]
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[[ 0.05607819 -0.1270548   0.00318863 ..., -0.12365623  0.17462536
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 [ 0.06577873 -0.03761328 -0.08471291 ...,  0.03986696  0.1983188
   0.20094269]]
Progress: 1.8% ... Training loss: 0.421 ... Validation loss: 0.685[[ 0.21798291]
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[[ 0.05667565 -0.12765135  0.00132229 ..., -0.12380637  0.17635894
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   0.20044752]]
Progress: 1.8% ... Training loss: 0.420 ... Validation loss: 0.658[[  2.08671672e-01]
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[[ 0.05622602 -0.12729796  0.00254233 ..., -0.12374528  0.17512794
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 [ 0.038573    0.05010344  0.12343008 ..., -0.24323298 -0.05161369
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 [-0.19517798 -0.17433445 -0.1086476  ...,  0.11227681 -0.04526564
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 [ 0.06584426 -0.03771068 -0.08497374 ...,  0.03984307  0.19856535
   0.20067088]]
Progress: 1.8% ... Training loss: 0.405 ... Validation loss: 0.657[[ 0.21101491]
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[[ 0.05639323 -0.12743043  0.0021313  ..., -0.1237719   0.17544633
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 [ 0.03864727  0.05003962  0.12323855 ..., -0.24324661 -0.0514216
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   0.20054589]]
Progress: 1.8% ... Training loss: 0.405 ... Validation loss: 0.653[[ 0.19423558]
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[[ 0.05545809 -0.12665488  0.00489519 ..., -0.12361692  0.17298431
  -0.17722618]
 [ 0.03859911  0.05008155  0.12338006 ..., -0.24323818 -0.05155279
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 [ 0.06556521 -0.03749761 -0.08415524 ...,  0.03989242  0.19800983
   0.20137589]]
Progress: 1.8% ... Training loss: 0.448 ... Validation loss: 0.721[[ 0.21990753]
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[[ 0.05638212 -0.12763136  0.00186744 ..., -0.12386417  0.17547133
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 [ 0.0386661   0.05001273  0.12315775 ..., -0.24325619 -0.0513777
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   0.20094276]]
Progress: 1.8% ... Training loss: 0.417 ... Validation loss: 0.656[[ 0.20549442]
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[[ 0.0555071  -0.12692256  0.00439471 ..., -0.12375171  0.17302245
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 [ 0.03864098  0.05003326  0.12323184 ..., -0.24325295 -0.05145251
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 [ 0.06528493 -0.03728894 -0.08338965 ...,  0.03991302  0.19740514
   0.20203354]]
Progress: 1.8% ... Training loss: 0.407 ... Validation loss: 0.665[[  2.17755777e-01]
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[[ 0.05577932 -0.12715493  0.00360954 ..., -0.12380398  0.1736878
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 [ 0.0386476   0.05002466  0.12320701 ..., -0.24325435 -0.05142703
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 [-0.19483009 -0.17471852 -0.1097599  ...,  0.11216092 -0.04437252
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 [ 0.06528137 -0.03728456 -0.08336164 ...,  0.03991507  0.19741614
   0.20203645]]
Progress: 1.8% ... Training loss: 0.407 ... Validation loss: 0.650[[ 0.20414791]
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[[ 0.05502969 -0.1265156   0.00594211 ..., -0.12369952  0.17180802
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   0.20311362]]
Progress: 1.8% ... Training loss: 0.409 ... Validation loss: 0.668[[ 0.21729131]
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[[ 0.0552772  -0.12675971  0.0052406  ..., -0.12375884  0.17249612
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   0.20316873]]
Progress: 1.8% ... Training loss: 0.404 ... Validation loss: 0.647[[ 0.20763105]
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[[ 0.05524805 -0.1267122   0.00551299 ..., -0.12374696  0.17214263
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   0.20450366]]
Progress: 1.8% ... Training loss: 0.401 ... Validation loss: 0.654[[ 0.20753555]
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[[ 0.05507323 -0.12654668  0.00626518 ..., -0.12370228  0.171444
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   0.20422733]]
Progress: 1.9% ... Training loss: 0.401 ... Validation loss: 0.653[[ 0.22531697]
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[[ 0.05545712 -0.12690567  0.00519435 ..., -0.12377706  0.17252711
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 [ 0.06429438 -0.03642575 -0.08039332 ...,  0.04007602  0.19509001
   0.20468112]]
Progress: 1.9% ... Training loss: 0.423 ... Validation loss: 0.653[[ 0.20852575]
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[[ 0.05488391 -0.12644683  0.00693682 ..., -0.12369534  0.17101083
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   0.20598037]]
Progress: 1.9% ... Training loss: 0.399 ... Validation loss: 0.651[[ 0.21793144]
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[[ 0.05489195 -0.12645011  0.00704239 ..., -0.12369339  0.17100275
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 [ 0.06405148 -0.03627302 -0.07976751 ...,  0.04008504  0.19461507
   0.20527148]]
Progress: 1.9% ... Training loss: 0.400 ... Validation loss: 0.641[[ 0.21092119]
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[[ 0.0544433  -0.12609266  0.00821039 ..., -0.12361399  0.16977914
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   0.20533856]]
Progress: 1.9% ... Training loss: 0.396 ... Validation loss: 0.646[[ 0.21556724]
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[[ 0.05447554 -0.12612414  0.00819655 ..., -0.12362664  0.16995039
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   0.20471435]]
Progress: 1.9% ... Training loss: 0.394 ... Validation loss: 0.640[[ 0.20163443]
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[[ 0.05341793 -0.12522826  0.01137072 ..., -0.12341248  0.16701988
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   0.20517514]]
Progress: 1.9% ... Training loss: 0.422 ... Validation loss: 0.685[[ 0.22487822]
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[[ 0.05403571 -0.12583882  0.00942737 ..., -0.12358632  0.16858146
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   0.20421394]]
Progress: 1.9% ... Training loss: 0.408 ... Validation loss: 0.648[[ 0.19034578]
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[[ 0.05173945 -0.1240448   0.01586568 ..., -0.12316246  0.16267347
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   0.20526919]]
Progress: 1.9% ... Training loss: 0.503 ... Validation loss: 0.778[[ 0.23388581]
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[[ 0.05319129 -0.12560776  0.01099406 ..., -0.12369381  0.16691245
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   0.20324865]]
Progress: 1.9% ... Training loss: 0.444 ... Validation loss: 0.681[[ 0.20919373]
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[[ 0.05198611 -0.12472686  0.01442612 ..., -0.1235212   0.16373245
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 [-0.19425772 -0.17550117 -0.11193981 ...,  0.1118683  -0.04298695
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 [ 0.06394147 -0.036534   -0.08000235 ...,  0.03991681  0.19495441
   0.20482655]]
Progress: 1.9% ... Training loss: 0.401 ... Validation loss: 0.653[[ 0.2245588 ]
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[[ 0.05263916 -0.12534889  0.01248911 ..., -0.12370444  0.16558656
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   0.20458571]]
Progress: 1.9% ... Training loss: 0.396 ... Validation loss: 0.640[[ 0.20128623]
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   0.20528932]]
Progress: 1.9% ... Training loss: 0.440 ... Validation loss: 0.697[[  2.27655856e-01]
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 [ -6.41142746e-01]
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[[ 0.05224575 -0.12522134  0.01335039 ..., -0.12374015  0.16464551
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   0.20322966]]
Progress: 1.9% ... Training loss: 0.399 ... Validation loss: 0.643[[ 0.21399913]
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[[ 0.0516478  -0.12475376  0.01507569 ..., -0.123622    0.16308956
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   0.20349325]]
Progress: 1.9% ... Training loss: 0.393 ... Validation loss: 0.639[[ 0.22436204]
 [-0.18022376]
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[[ 0.05182096 -0.12491619  0.01464904 ..., -0.12367033  0.163397
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   0.2028988 ]]
Progress: 2.0% ... Training loss: 0.388 ... Validation loss: 0.630[[ 0.21859149]
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[[ 0.05226301 -0.12525927  0.0136093  ..., -0.12375134  0.16428826
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   0.20260523]]
Progress: 2.0% ... Training loss: 0.385 ... Validation loss: 0.628[[ 0.21808582]
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[[ 0.05224526 -0.12522706  0.01375737 ..., -0.12373469  0.16407653
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   0.20287501]]
Progress: 2.0% ... Training loss: 0.384 ... Validation loss: 0.629[[ 0.21367727]
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   0.20183653]]
Progress: 2.0% ... Training loss: 0.386 ... Validation loss: 0.633[[ 0.21267032]
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[[ 0.05250686 -0.12539739  0.0132779  ..., -0.12378664  0.16448922
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 [ 0.06471464 -0.03731374 -0.08250966 ...,  0.03966594  0.19738223
   0.20252586]]
Progress: 2.0% ... Training loss: 0.385 ... Validation loss: 0.630[[ 0.22970967]
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[[ 0.05362322 -0.12639351  0.01009462 ..., -0.12408847  0.16746079
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   0.20092368]]
Progress: 2.0% ... Training loss: 0.409 ... Validation loss: 0.647[[ 0.22324966]
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[[ 0.05359872 -0.12637834  0.01015113 ..., -0.12408708  0.16718571
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   0.20091304]]
Progress: 2.0% ... Training loss: 0.385 ... Validation loss: 0.620[[  2.21824985e-01]
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[[ 0.05373751 -0.12648929  0.00986745 ..., -0.12412277  0.1672955
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 [ 0.06545579 -0.03798313 -0.08474707 ...,  0.0394711   0.1994553
   0.20041488]]
Progress: 2.0% ... Training loss: 0.381 ... Validation loss: 0.616[[ 0.22429421]
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[[ 0.05351657 -0.12629332  0.01085143 ..., -0.12406312  0.16647992
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 [ 0.06554148 -0.03806237 -0.08495513 ...,  0.03944623  0.1997342
   0.20017192]]
Progress: 2.0% ... Training loss: 0.384 ... Validation loss: 0.613[[ 0.21540968]
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[[ 0.05286866 -0.12575747  0.01283764 ..., -0.1239209   0.16463052
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 [-0.19510073 -0.1749372  -0.10959402 ...,  0.11197441 -0.04581399
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 [ 0.06547438 -0.03799538 -0.08472983 ...,  0.03946783  0.19959897
   0.20039658]]
Progress: 2.0% ... Training loss: 0.378 ... Validation loss: 0.616[[ 0.22371414]
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[[ 0.05297261 -0.12588042  0.01260704 ..., -0.1239551   0.16492431
  -0.1717968 ]
 [ 0.03864945  0.04995012  0.12300295 ..., -0.24326711 -0.0512384
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 [-0.19559752 -0.17450753 -0.108115   ...,  0.11210276 -0.04720037
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 [ 0.06545587 -0.03797152 -0.08460853 ...,  0.03947345  0.19952388
   0.20044268]]
Progress: 2.0% ... Training loss: 0.381 ... Validation loss: 0.614[[ 0.21618621]
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[[ 0.05280332 -0.12576349  0.01309689 ..., -0.12391897  0.16440271
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Progress: 2.0% ... Training loss: 0.377 ... Validation loss: 0.614[[ 0.22914068]
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[[ 0.05343791 -0.12635547  0.01117436 ..., -0.12410506  0.16623594
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   0.20166865]]
Progress: 2.0% ... Training loss: 0.386 ... Validation loss: 0.616[[ 0.2130972 ]
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[[ 0.05243338 -0.12555791  0.0141399  ..., -0.12388486  0.16343482
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   0.20098587]]
Progress: 2.0% ... Training loss: 0.387 ... Validation loss: 0.627[[ 0.21993272]
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   0.19988534]]
Progress: 2.0% ... Training loss: 0.374 ... Validation loss: 0.610[[ 0.21967605]
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[[ 0.0520612  -0.12524725  0.01531442 ..., -0.12377756  0.16236089
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   0.20082605]]
Progress: 2.1% ... Training loss: 0.374 ... Validation loss: 0.613[[ 0.21877384]
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[[ 0.05149664 -0.12473807  0.01716563 ..., -0.12361561  0.16064655
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   0.20015536]]
Progress: 2.1% ... Training loss: 0.374 ... Validation loss: 0.612[[ 0.21850243]
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   0.20025871]]
Progress: 2.1% ... Training loss: 0.373 ... Validation loss: 0.610[[ 0.23869638]
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   0.19931203]]
Progress: 2.1% ... Training loss: 0.413 ... Validation loss: 0.643[[ 0.22252793]
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[[ 0.05236154 -0.1255981   0.01478785 ..., -0.12392605  0.16301    -0.17017548]
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   0.20017389]]
Progress: 2.1% ... Training loss: 0.370 ... Validation loss: 0.601[[ 0.22501669]
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[[ 0.05244165 -0.12568258  0.01455279 ..., -0.12395109  0.162998
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   0.19973066]]
Progress: 2.1% ... Training loss: 0.369 ... Validation loss: 0.599[[ 0.22225329]
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[[ 0.05233739 -0.12558004  0.01494734 ..., -0.12391278  0.16259642
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   0.19995508]]
Progress: 2.1% ... Training loss: 0.369 ... Validation loss: 0.601[[ 0.22708012]
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[[ 0.05259935 -0.12580671  0.01445884 ..., -0.12397799  0.16318163
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   0.20071793]]
Progress: 2.1% ... Training loss: 0.369 ... Validation loss: 0.596[[ 0.21949311]
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[[ 0.05204541 -0.12534907  0.01612044 ..., -0.12383511  0.16169053
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   0.2001282 ]]
Progress: 2.1% ... Training loss: 0.373 ... Validation loss: 0.602[[ 0.23907257]
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[[ 0.05300502 -0.12619728  0.01325906 ..., -0.12411774  0.16415026
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   0.19998518]]
Progress: 2.1% ... Training loss: 0.401 ... Validation loss: 0.618[[ 0.21255073]
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[[ 0.05174758 -0.12524123  0.01693286 ..., -0.12386046  0.16068847
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   0.20041702]]
Progress: 2.1% ... Training loss: 0.393 ... Validation loss: 0.625[[ 0.24222562]
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[[ 0.05345849 -0.12685235  0.01161056 ..., -0.1244342   0.16539495
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 [ 0.06579898 -0.038359   -0.08581498 ...,  0.03931185  0.20131817
   0.19926599]]
Progress: 2.1% ... Training loss: 0.419 ... Validation loss: 0.639[[ 0.22806235]
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[[ 0.05359651 -0.1269467   0.01135225 ..., -0.1244598   0.16555819
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   0.19990065]]
Progress: 2.1% ... Training loss: 0.366 ... Validation loss: 0.588[[ 0.22146399]
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[[ 0.05298768 -0.12643395  0.01328364 ..., -0.12429789  0.16385256
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 [ 0.06567081 -0.03826122 -0.08539013 ...,  0.0393301   0.20108833
   0.1996316 ]]
Progress: 2.1% ... Training loss: 0.365 ... Validation loss: 0.589[[  2.27802539e-01]
 [ -1.87948030e-01]
 [ -6.80171626e-01]
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[[ 0.0531019  -0.12655549  0.01285143 ..., -0.12433872  0.16427621
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 [ 0.06565078 -0.0382409  -0.0852942  ...,  0.03933707  0.20117474
   0.19972727]]
Progress: 2.1% ... Training loss: 0.363 ... Validation loss: 0.583[[ 0.21813033]
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[[ 0.05216656 -0.12577238  0.0156639  ..., -0.12409157  0.16159517
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 [ 0.06558558 -0.0381831  -0.08505874 ...,  0.03934731  0.20089089
   0.19984559]]
Progress: 2.2% ... Training loss: 0.375 ... Validation loss: 0.601[[ 0.25105757]
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[[ 0.05442314 -0.12787085  0.00849968 ..., -0.12481695  0.1681139
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 [ 0.06582415 -0.03840795 -0.08581761 ...,  0.03927497  0.20164935
   0.19916934]]
Progress: 2.2% ... Training loss: 0.466 ... Validation loss: 0.680[[ 0.22677799]
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[[ 0.05360837 -0.1273158   0.01074272 ..., -0.12468137  0.16599037
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 [ 0.06529128 -0.0380487  -0.08439311 ...,  0.03936418  0.20028716
   0.2003936 ]]
Progress: 2.2% ... Training loss: 0.361 ... Validation loss: 0.576[[ 0.23523142]
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[[ 0.05410203 -0.12777247  0.00927812 ..., -0.12481887  0.16713684
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 [ 0.06604102 -0.03871974 -0.08666626 ...,  0.03915563  0.2023857
   0.19826059]]
Progress: 2.2% ... Training loss: 0.370 ... Validation loss: 0.582[[ 0.21882592]
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[[ 0.05358104 -0.12734288  0.01104582 ..., -0.12468199  0.16567703
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 [ 0.06529365 -0.03810627 -0.08452595 ...,  0.03933629  0.20042458
   0.20023607]]
Progress: 2.2% ... Training loss: 0.373 ... Validation loss: 0.592[[ 0.23536354]
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[[ 0.05418236 -0.12788595  0.00952637 ..., -0.1248668   0.16708361
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 [ 0.06561252 -0.03841025 -0.0854155  ...,  0.03923264  0.20124013
   0.19928787]]
Progress: 2.2% ... Training loss: 0.370 ... Validation loss: 0.579[[ 0.22509487]
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[[ 0.05357045 -0.12740284  0.01139879 ..., -0.12473906  0.16530261
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 [ 0.0655339  -0.03835336 -0.08511563 ...,  0.03924924  0.20101257
   0.19946941]]
Progress: 2.2% ... Training loss: 0.360 ... Validation loss: 0.574[[ 0.22896704]
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[[ 0.05336396 -0.12725331  0.01200377 ..., -0.12469494  0.16473758
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 [ 0.06565923 -0.03846986 -0.08551907 ...,  0.03920832  0.20136751
   0.19908967]]
Progress: 2.2% ... Training loss: 0.358 ... Validation loss: 0.571[[ 0.22346458]
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[[ 0.05304469 -0.12697161  0.01303461 ..., -0.12460946  0.16379788
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 [ 0.06557024 -0.03839096 -0.08523531 ...,  0.03922718  0.20112658
   0.19931861]]
Progress: 2.2% ... Training loss: 0.361 ... Validation loss: 0.579[[  2.32756079e-01]
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[[ 0.05303084 -0.12694961  0.01317411 ..., -0.1246097   0.16372269
  -0.1721009 ]
 [ 0.0375821   0.0507931   0.12598782 ..., -0.24302333 -0.05412193
   0.13071174]
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 [-0.19508073 -0.17535329 -0.11010405 ...,  0.1116613  -0.04619684
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 [ 0.06566174 -0.0384765  -0.08555612 ...,  0.03918963  0.20141784
   0.1989943 ]]
Progress: 2.2% ... Training loss: 0.358 ... Validation loss: 0.573[[ 0.23178415]
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[[ 0.05271606 -0.12670722  0.01406713 ..., -0.12452075  0.16294562
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Progress: 2.2% ... Training loss: 0.356 ... Validation loss: 0.575[[ 0.2292726 ]
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   0.1995309 ]]
Progress: 2.2% ... Training loss: 0.355 ... Validation loss: 0.575[[ 0.23334365]
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[[ 0.05325156 -0.12719092  0.01266925 ..., -0.12468451  0.16445834
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   0.20023693]]
Progress: 2.2% ... Training loss: 0.356 ... Validation loss: 0.573[[ 0.22523028]
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[[ 0.05277689 -0.12679374  0.01422065 ..., -0.12456172  0.16316546
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   0.20077389]]
Progress: 2.2% ... Training loss: 0.360 ... Validation loss: 0.578[[ 0.23062501]
 [-0.19791677]
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[[ 0.05279924 -0.12684083  0.01410587 ..., -0.12457323  0.16332894
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 [ 0.06494999 -0.03785808 -0.08334664 ...,  0.03939818  0.19961987
   0.20095893]]
Progress: 2.2% ... Training loss: 0.354 ... Validation loss: 0.571[[ 0.23916333]
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[[ 0.05317303 -0.127153    0.0129783  ..., -0.1246736   0.16416526
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   0.19949164]]
Progress: 2.3% ... Training loss: 0.363 ... Validation loss: 0.575[[ 0.21866864]
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   0.20069105]]
Progress: 2.3% ... Training loss: 0.382 ... Validation loss: 0.599[[ 0.2508665 ]
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   0.19998222]]
Progress: 2.3% ... Training loss: 0.414 ... Validation loss: 0.624[[ 0.21752779]
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[[ 0.05203236 -0.12666318  0.0157683  ..., -0.12467103  0.1611534
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   0.2007176 ]]
Progress: 2.3% ... Training loss: 0.393 ... Validation loss: 0.614[[ 0.24823454]
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[[ 0.05369231 -0.12830175  0.01050845 ..., -0.12527581  0.16603571
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   0.19873544]]
Progress: 2.3% ... Training loss: 0.385 ... Validation loss: 0.596[[ 0.22842585]
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[[ 0.05218816 -0.12715738  0.01481591 ..., -0.12496248  0.16203217
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   0.20058432]]
Progress: 2.3% ... Training loss: 0.358 ... Validation loss: 0.573[[  2.40308013e-01]
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[[ 0.05268897 -0.12762759  0.01326144 ..., -0.12511701  0.1635054
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 [ 0.06540694 -0.03853543 -0.0852604  ...,  0.03910389  0.2016776
   0.19925215]]
Progress: 2.3% ... Training loss: 0.354 ... Validation loss: 0.564[[ 0.23673549]
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[[ 0.0527386  -0.12767374  0.01329108 ..., -0.12513223  0.16346851
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   0.20023557]]
Progress: 2.3% ... Training loss: 0.350 ... Validation loss: 0.562[[ 0.23228428]
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[[ 0.05199868 -0.12704609  0.01561025 ..., -0.12493472  0.16139948
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   0.20023987]]
Progress: 2.3% ... Training loss: 0.351 ... Validation loss: 0.567[[ 0.24155534]
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[[ 0.05263746 -0.12760487  0.01389068 ..., -0.12511452  0.1631475
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 [ 0.065157   -0.03833231 -0.08446261 ...,  0.03915146  0.20112769
   0.19991202]]
Progress: 2.3% ... Training loss: 0.352 ... Validation loss: 0.566[[ 0.23361681]
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   0.19949311]]
Progress: 2.3% ... Training loss: 0.350 ... Validation loss: 0.563[[ 0.2360683 ]
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   0.19916403]]
Progress: 2.3% ... Training loss: 0.349 ... Validation loss: 0.560[[ 0.23700016]
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[[ 0.05166211 -0.12678828  0.01705685 ..., -0.1248662   0.16053113
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   0.19897849]]
Progress: 2.3% ... Training loss: 0.349 ... Validation loss: 0.561[[ 0.24520641]
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[[ 0.05145268 -0.12662288  0.01787924 ..., -0.12482674  0.16007132
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   0.1994963 ]]
Progress: 2.3% ... Training loss: 0.351 ... Validation loss: 0.562[[ 0.23823584]
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[[ 0.05129208 -0.12647343  0.01864771 ..., -0.12478466  0.1592208
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   0.19970122]]
Progress: 2.3% ... Training loss: 0.348 ... Validation loss: 0.559[[  2.49123201e-01]
 [ -1.94253668e-01]
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[[ 0.0519173  -0.12702939  0.01692464 ..., -0.12496758  0.16090828
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   0.19914854]]
Progress: 2.4% ... Training loss: 0.356 ... Validation loss: 0.565[[ 0.23848452]
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[[ 0.05163371 -0.12678418  0.0179614  ..., -0.12491531  0.15990588
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   0.19866585]]
Progress: 2.4% ... Training loss: 0.347 ... Validation loss: 0.554[[ 0.24381357]
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   0.19912761]]
Progress: 2.4% ... Training loss: 0.346 ... Validation loss: 0.549[[ 0.2426691 ]
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   0.19842779]]
Progress: 2.4% ... Training loss: 0.345 ... Validation loss: 0.548[[ 0.23039925]
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[[ 0.05071351 -0.1259753   0.02119027 ..., -0.12465217  0.15667443
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   0.1990825 ]]
Progress: 2.4% ... Training loss: 0.362 ... Validation loss: 0.574[[ 0.24896176]
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[[ 0.05169689 -0.12688869  0.01808165 ..., -0.12496176  0.15932187
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   0.19836141]]
Progress: 2.4% ... Training loss: 0.353 ... Validation loss: 0.554[[ 0.23646641]
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[[ 0.05136915 -0.12662084  0.01926737 ..., -0.12487434  0.15830393
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   0.19878137]]
Progress: 2.4% ... Training loss: 0.346 ... Validation loss: 0.553[[ 0.25324134]
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[[ 0.05245105 -0.12760513  0.01590753 ..., -0.12518116  0.16137657
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   0.19836138]]
Progress: 2.4% ... Training loss: 0.363 ... Validation loss: 0.569[[ 0.23138468]
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[[ 0.05112213 -0.12657311  0.01961922 ..., -0.12489937  0.15776698
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   0.19915631]]
Progress: 2.4% ... Training loss: 0.367 ... Validation loss: 0.573[[ 0.2449959 ]
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[[ 0.051905   -0.12732382  0.01735054 ..., -0.125129    0.1598267
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   0.1985152 ]]
Progress: 2.4% ... Training loss: 0.342 ... Validation loss: 0.551[[ 0.23896782]
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[[ 0.05189977 -0.12731169  0.0176547  ..., -0.1251319   0.15965281
  -0.16953276]
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   0.19858315]]
Progress: 2.4% ... Training loss: 0.343 ... Validation loss: 0.552[[ 0.2464198 ]
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[[ 0.05181374 -0.12724904  0.01797341 ..., -0.1251099   0.15929317
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 [ 0.06548156 -0.03868693 -0.08530038 ...,  0.03900105  0.20300315
   0.19877226]]
Progress: 2.4% ... Training loss: 0.342 ... Validation loss: 0.551[[ 0.2395789 ]
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[[ 0.05092759 -0.12650455  0.02060122 ..., -0.12487532  0.15669679
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   0.19922995]]
Progress: 2.4% ... Training loss: 0.342 ... Validation loss: 0.552[[ 0.2493592 ]
 [-0.19973329]
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[[ 0.05200738 -0.12748121  0.0172563  ..., -0.12518806  0.15967851
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  -0.23117185]
 [ 0.06537681 -0.03857934 -0.0849803  ...,  0.03903563  0.20275592
   0.19909513]]
Progress: 2.4% ... Training loss: 0.346 ... Validation loss: 0.554[[ 0.25712134]
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[[ 0.05305755 -0.12834845  0.01428507 ..., -0.12544331  0.16257039
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 [ 0.0659424  -0.0390545  -0.08664107 ...,  0.03888628  0.2043807
   0.19755024]]
Progress: 2.4% ... Training loss: 0.369 ... Validation loss: 0.571[[ 0.24074162]
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[[ 0.05260835 -0.1279669   0.01569994 ..., -0.12533346  0.16114669
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 [ 0.06597347 -0.03906945 -0.08669102 ...,  0.03888774  0.20449051
   0.19751767]]
Progress: 2.5% ... Training loss: 0.341 ... Validation loss: 0.540[[ 0.24251864]
 [-0.20702254]
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[[ 0.05294603 -0.12824701  0.01480188 ..., -0.12540948  0.16203955
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   0.19697099]]
Progress: 2.5% ... Training loss: 0.339 ... Validation loss: 0.538[[ 0.2358585 ]
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[[ 0.05275354 -0.12808899  0.01541767 ..., -0.12535864  0.16156687
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   0.1971769 ]]
Progress: 2.5% ... Training loss: 0.347 ... Validation loss: 0.549[[ 0.24453596]
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[[ 0.05227682 -0.12764424  0.01692016 ..., -0.12521159  0.16022307
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 [ 0.06602858 -0.03908411 -0.08673293 ...,  0.03888175  0.20482339
   0.19750837]]
Progress: 2.5% ... Training loss: 0.338 ... Validation loss: 0.542[[ 0.2424412 ]
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[[ 0.05243385 -0.12778383  0.01666012 ..., -0.12525734  0.16056528
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 [ 0.06560437 -0.03869748 -0.08538066 ...,  0.03899941  0.20369473
   0.19866823]]
Progress: 2.5% ... Training loss: 0.337 ... Validation loss: 0.541[[ 0.2434341 ]
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[[ 0.05287965 -0.12818974  0.01547118 ..., -0.12538421  0.16164142
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   0.19859575]]
Progress: 2.5% ... Training loss: 0.337 ... Validation loss: 0.541[[ 0.25013276]
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[[ 0.05313495 -0.12841761  0.01467245 ..., -0.12546153  0.16243559
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 [-0.1923753  -0.17796957 -0.1178307  ...,  0.11057867 -0.04031789
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  -0.23007345]
 [ 0.06588743 -0.03895787 -0.08627195 ...,  0.03891883  0.20458707
   0.19785877]]
Progress: 2.5% ... Training loss: 0.342 ... Validation loss: 0.544[[ 0.24741386]
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[[ 0.05284515 -0.12818852  0.01549399 ..., -0.12539197  0.16167193
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 [ 0.06633966 -0.03934029 -0.08762596 ...,  0.03879714  0.20598386
   0.19670858]]
Progress: 2.5% ... Training loss: 0.337 ... Validation loss: 0.537[[ 0.2404265 ]
 [-0.21246148]
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[[  5.22703364e-02  -1.27689576e-01   1.71700922e-02 ...,  -1.25235568e-01
    1.60032384e-01  -1.70015544e-01]
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   -5.26553284e-02   1.29256052e-01]
 [  1.76367004e-02  -1.27876452e-02  -1.92644408e-01 ...,   1.61407181e-01
    1.19204014e-01   1.09657573e-01]
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 [ -1.92431306e-01  -1.77931007e-01  -1.17641560e-01 ...,   1.10587356e-01
   -4.05009095e-02  -1.91128689e-02]
 [ -2.77871346e-01  -2.19077751e-01  -4.39837167e-02 ...,  -1.14572353e-01
    1.54564692e-04  -2.29202234e-01]
 [  6.61789950e-02  -3.92018181e-02  -8.71581822e-02 ...,   3.88440868e-02
    2.05558871e-01   1.97153342e-01]]
Progress: 2.5% ... Training loss: 0.341 ... Validation loss: 0.543[[ 0.25636946]
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Progress: 2.5% ... Training loss: 0.354 ... Validation loss: 0.546[[ 0.23099419]
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   0.19642066]]
Progress: 2.5% ... Training loss: 0.382 ... Validation loss: 0.587[[ 0.2623532 ]
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   0.19414408]]
Progress: 2.5% ... Training loss: 0.373 ... Validation loss: 0.571[[ 0.22908373]
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[[ 0.05113593 -0.12728398  0.0194949  ..., -0.1252946   0.15732057
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   0.19479091]]
Progress: 2.5% ... Training loss: 0.402 ... Validation loss: 0.607[[ 0.25298896]
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   0.19486194]]
Progress: 2.5% ... Training loss: 0.338 ... Validation loss: 0.542[[ 0.25181678]
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[[ 0.05250653 -0.12862798  0.01539634 ..., -0.12579645  0.16113922
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   0.19509986]]
Progress: 2.5% ... Training loss: 0.335 ... Validation loss: 0.539[[ 0.25232673]
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   0.19507792]]
Progress: 2.6% ... Training loss: 0.335 ... Validation loss: 0.540[[ 0.25006117]
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   0.19590114]]
Progress: 2.6% ... Training loss: 0.333 ... Validation loss: 0.537[[ 0.24825777]
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   0.19615859]]
Progress: 2.6% ... Training loss: 0.333 ... Validation loss: 0.537[[ 0.24192445]
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   0.1966603 ]]
Progress: 2.6% ... Training loss: 0.341 ... Validation loss: 0.544[[ 0.25500375]
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[[ 0.05185872 -0.12806473  0.0180222  ..., -0.12563017  0.1591008
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   0.19652619]]
Progress: 2.6% ... Training loss: 0.338 ... Validation loss: 0.547[[ 0.24791089]
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[[ 0.05151744 -0.12777437  0.01908483 ..., -0.12553841  0.15808697
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   0.19675645]]
Progress: 2.6% ... Training loss: 0.333 ... Validation loss: 0.535[[ 0.25289777]
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   0.19620727]]
Progress: 2.6% ... Training loss: 0.334 ... Validation loss: 0.538[[ 0.25201983]
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[[ 0.05149923 -0.1277342   0.01948856 ..., -0.12554012  0.1577895
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   0.19757398]]
Progress: 2.6% ... Training loss: 0.331 ... Validation loss: 0.530[[ 0.25844191]
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[[ 0.05218648 -0.12830728  0.0176013  ..., -0.12575039  0.15964537
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   0.19847008]]
Progress: 2.6% ... Training loss: 0.341 ... Validation loss: 0.537[[ 0.23541427]
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Progress: 2.6% ... Training loss: 0.377 ... Validation loss: 0.572[[  2.65273046e-01]
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Progress: 2.6% ... Training loss: 0.363 ... Validation loss: 0.556[[ 0.24486961]
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   0.20016749]]
Progress: 2.6% ... Training loss: 0.339 ... Validation loss: 0.530[[ 0.26345667]
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   0.19968868]]
Progress: 2.6% ... Training loss: 0.354 ... Validation loss: 0.534[[ 0.24006601]
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   0.20015454]]
Progress: 2.6% ... Training loss: 0.357 ... Validation loss: 0.547[[ 0.25847669]
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[[ 0.05143588 -0.12815758  0.0193991  ..., -0.12582748  0.15738808
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   0.20084413]]
Progress: 2.6% ... Training loss: 0.337 ... Validation loss: 0.527[[ 0.24046839]
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[[ 0.05054363 -0.12741164  0.0219442  ..., -0.12559835  0.15511955
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Progress: 2.7% ... Training loss: 0.353 ... Validation loss: 0.543[[ 0.25590721]
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Progress: 2.7% ... Training loss: 0.329 ... Validation loss: 0.521[[  2.62330263e-01]
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   0.20209587]]
Progress: 2.7% ... Training loss: 0.342 ... Validation loss: 0.532[[ 0.2405013 ]
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   0.20292906]]
Progress: 2.7% ... Training loss: 0.352 ... Validation loss: 0.540[[  2.60619987e-01]
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[[ 0.05221239 -0.12909822  0.01725437 ..., -0.12615712  0.15955463
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   0.20136942]]
Progress: 2.7% ... Training loss: 0.340 ... Validation loss: 0.532[[ 0.23487819]
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[[ 0.05034973 -0.12752928  0.02244762 ..., -0.12571107  0.15476086
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   0.20278631]]
Progress: 2.7% ... Training loss: 0.379 ... Validation loss: 0.568[[ 0.26463571]
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[[ 0.05176245 -0.12898513  0.01797463 ..., -0.12621999  0.15859008
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   0.20102681]]
Progress: 2.7% ... Training loss: 0.356 ... Validation loss: 0.553[[ 0.25178316]
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[[ 0.05119958 -0.12855466  0.01959865 ..., -0.12610674  0.15697514
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   0.20182256]]
Progress: 2.7% ... Training loss: 0.326 ... Validation loss: 0.515[[ 0.25698392]
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[[ 0.05071904 -0.1281275   0.02100532 ..., -0.12596924  0.15574429
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   0.20208329]]
Progress: 2.7% ... Training loss: 0.327 ... Validation loss: 0.519[[ 0.24789734]
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[[ 0.05060577 -0.1280411   0.02141567 ..., -0.12594768  0.15532438
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   0.20243734]]
Progress: 2.7% ... Training loss: 0.331 ... Validation loss: 0.520[[ 0.26464053]
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[[ 0.05117461 -0.12854788  0.01981685 ..., -0.12611036  0.15673645
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  -0.23416087]
 [ 0.06423277 -0.03791246 -0.08213051 ...,  0.03906048  0.20323078
   0.20141487]]
Progress: 2.7% ... Training loss: 0.344 ... Validation loss: 0.533[[ 0.25249921]
 [-0.22375024]
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[[ 0.05067687 -0.12813782  0.02140642 ..., -0.12598475  0.15547004
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  -0.23408637]
 [ 0.06410308 -0.03780017 -0.08172512 ...,  0.0390997   0.20304188
   0.20178277]]
Progress: 2.7% ... Training loss: 0.326 ... Validation loss: 0.513[[ 0.25899602]
 [-0.21929319]
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[[ 0.05070266 -0.128177    0.02146103 ..., -0.12599525  0.15543574
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   0.20068306]]
Progress: 2.7% ... Training loss: 0.326 ... Validation loss: 0.516[[ 0.25602499]
 [-0.22057965]
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[[ 0.05074221 -0.12822846  0.02156046 ..., -0.12601415  0.15552471
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   0.20081129]]
Progress: 2.7% ... Training loss: 0.324 ... Validation loss: 0.515[[ 0.25482206]
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[[ 0.05103124 -0.12844426  0.02096222 ..., -0.1260985   0.15634137
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 [ 0.06499394 -0.03859344 -0.08436664 ...,  0.03884287  0.20569437
   0.19928723]]
Progress: 2.7% ... Training loss: 0.324 ... Validation loss: 0.513[[ 0.25838619]
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[[ 0.05137946 -0.12875021  0.02013731 ..., -0.12620827  0.15708792
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   0.19868914]]
Progress: 2.8% ... Training loss: 0.325 ... Validation loss: 0.512[[ 0.25669074]
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[[ 0.0511624  -0.1285938   0.02074145 ..., -0.12615461  0.15660844
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   0.1987517 ]]
Progress: 2.8% ... Training loss: 0.323 ... Validation loss: 0.512[[ 0.25181795]
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[[ 0.05109076 -0.12853278  0.02114349 ..., -0.12613745  0.15633784
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 [ 0.06527794 -0.03881914 -0.08517709 ...,  0.03876185  0.20652861
   0.19861126]]
Progress: 2.8% ... Training loss: 0.327 ... Validation loss: 0.519[[ 0.26080129]
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[[ 0.05095683 -0.12840496  0.02161373 ..., -0.12610204  0.15590465
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 [ 0.06488263 -0.038436   -0.08393239 ...,  0.038886    0.20554745
   0.19973322]]
Progress: 2.8% ... Training loss: 0.324 ... Validation loss: 0.519[[ 0.25662928]
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[[ 0.05059302 -0.12809747  0.02264732 ..., -0.12602005  0.15485887
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   0.19963655]]
Progress: 2.8% ... Training loss: 0.323 ... Validation loss: 0.512[[ 0.252545  ]
 [-0.22829794]
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[[ 0.05037891 -0.12788799  0.02344015 ..., -0.12595314  0.15411559
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 [ 0.06501985 -0.0385404  -0.08433389 ...,  0.03884518  0.20604137
   0.19946171]]
Progress: 2.8% ... Training loss: 0.327 ... Validation loss: 0.515[[  2.68537062e-01]
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[[ 0.0513013  -0.12870928  0.0209483  ..., -0.12622074  0.156592
  -0.16853975]
 [ 0.03831714  0.05000627  0.1232992  ..., -0.24331088 -0.05161361
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 [-0.19324431 -0.17780635 -0.11545347 ...,  0.11042947 -0.04337753
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   0.19970696]]
Progress: 2.8% ... Training loss: 0.342 ... Validation loss: 0.537[[ 0.25882701]
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[[ 0.05142352 -0.12883663  0.02072955 ..., -0.12625867  0.15677138
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Progress: 2.8% ... Training loss: 0.321 ... Validation loss: 0.511[[ 0.26486856]
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[[ 0.05191474 -0.12929301  0.01940003 ..., -0.12640099  0.15789541
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   0.19982353]]
Progress: 2.8% ... Training loss: 0.326 ... Validation loss: 0.512[[ 0.26485873]
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   0.19992918]]
Progress: 2.8% ... Training loss: 0.323 ... Validation loss: 0.508[[ 0.26454175]
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   0.19948838]]
Progress: 2.8% ... Training loss: 0.321 ... Validation loss: 0.505[[ 0.26473214]
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   0.2004057 ]]
Progress: 2.8% ... Training loss: 0.321 ... Validation loss: 0.501[[ 0.26656528]
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[[ 0.05207613 -0.12951817  0.0192863  ..., -0.12646792  0.15817377
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   0.19999113]]
Progress: 2.8% ... Training loss: 0.321 ... Validation loss: 0.505[[ 0.26481024]
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   0.1992489 ]]
Progress: 2.8% ... Training loss: 0.320 ... Validation loss: 0.503[[ 0.26516324]
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   0.19908395]]
Progress: 2.8% ... Training loss: 0.320 ... Validation loss: 0.502[[ 0.26071082]
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   0.19945073]]
Progress: 2.9% ... Training loss: 0.328 ... Validation loss: 0.510[[ 0.27023228]
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[[ 0.05139497 -0.12900754  0.02157151 ..., -0.12631999  0.15639333
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   0.19867102]]
Progress: 2.9% ... Training loss: 0.320 ... Validation loss: 0.502[[ 0.2586159 ]
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[[ 0.0507581  -0.12844055  0.02359199 ..., -0.12613847  0.15447839
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   0.19895969]]
Progress: 2.9% ... Training loss: 0.336 ... Validation loss: 0.517[[ 0.26634231]
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[[ 0.05122839 -0.12887676  0.02244335 ..., -0.12626844  0.15564887
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   0.20034627]]
Progress: 2.9% ... Training loss: 0.320 ... Validation loss: 0.499[[ 0.27797944]
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[[ 0.05175552 -0.12931424  0.02136139 ..., -0.12641184  0.1569316
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   0.20031517]]
Progress: 2.9% ... Training loss: 0.339 ... Validation loss: 0.510[[ 0.26741166]
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[[ 0.05086338 -0.12859236  0.02393338 ..., -0.12619135  0.15446879
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 [ 0.06469118 -0.03820397 -0.08310597 ...,  0.03896825  0.20632045
   0.20039137]]
Progress: 2.9% ... Training loss: 0.320 ... Validation loss: 0.496[[ 0.26894217]
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[[ 0.050647   -0.12841309  0.02459766 ..., -0.12613898  0.15396593
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   0.19957228]]
Progress: 2.9% ... Training loss: 0.321 ... Validation loss: 0.494[[ 0.27554053]
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   0.19984578]]
Progress: 2.9% ... Training loss: 0.327 ... Validation loss: 0.495[[ 0.26584349]
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   0.19992359]]
Progress: 2.9% ... Training loss: 0.323 ... Validation loss: 0.500[[ 0.27594956]
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[[ 0.05078079 -0.12860389  0.0242223  ..., -0.12620341  0.1543272
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   0.19947321]]
Progress: 2.9% ... Training loss: 0.324 ... Validation loss: 0.495[[ 0.27439079]
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[[ 0.05024624 -0.12816743  0.02583018 ..., -0.12606992  0.15279761
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   0.19896158]]
Progress: 2.9% ... Training loss: 0.320 ... Validation loss: 0.494[[ 0.2687623 ]
 [-0.23377079]
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[[ 0.0498376  -0.12780146  0.02704924 ..., -0.12597352  0.15152311
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   0.19983279]]
Progress: 2.9% ... Training loss: 0.318 ... Validation loss: 0.496[[ 0.26881174]
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[[ 0.05038804 -0.12829439  0.02545986 ..., -0.12610073  0.15290612
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   0.20010143]]
Progress: 2.9% ... Training loss: 0.317 ... Validation loss: 0.497[[ 0.26764004]
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[[ 0.05085307 -0.12868225  0.02442022 ..., -0.1262312   0.15406318
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   0.20045048]]
Progress: 2.9% ... Training loss: 0.317 ... Validation loss: 0.498[[ 0.26914844]
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   0.20034443]]
Progress: 2.9% ... Training loss: 0.317 ... Validation loss: 0.497[[ 0.26152189]
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[[ 0.05055773 -0.12840081  0.02555966 ..., -0.12615204  0.15307307
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   0.20216702]]
Progress: 3.0% ... Training loss: 0.327 ... Validation loss: 0.511[[ 0.27719648]
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[[ 0.05086797 -0.12871329  0.02467186 ..., -0.12625384  0.15402174
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   0.20260457]]
Progress: 3.0% ... Training loss: 0.325 ... Validation loss: 0.507[[ 0.27401741]
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[[ 0.05101927 -0.12880337  0.024278   ..., -0.12629545  0.15455413
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   0.20338247]]
Progress: 3.0% ... Training loss: 0.319 ... Validation loss: 0.499[[ 0.27451763]
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[[ 0.05062442 -0.12847145  0.02537648 ..., -0.12619668  0.153528
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   0.20403754]]
Progress: 3.0% ... Training loss: 0.318 ... Validation loss: 0.503[[ 0.27728498]
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[[ 0.05045112 -0.12832981  0.0259378  ..., -0.12615376  0.15300007
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 [ 0.06340909 -0.03706229 -0.07941117 ...,  0.03934022  0.20379293
   0.204069  ]]
Progress: 3.0% ... Training loss: 0.322 ... Validation loss: 0.504[[ 0.26321763]
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[[ 0.0496126  -0.12764747  0.02824099 ..., -0.12594996  0.15066211
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 [ 0.06284205 -0.03656765 -0.07785594 ...,  0.03948894  0.2023123
   0.20560129]]
Progress: 3.0% ... Training loss: 0.327 ... Validation loss: 0.510[[ 0.27570692]
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[[ 0.05035812 -0.12834906  0.02615399 ..., -0.12618972  0.15273461
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   0.20562205]]
Progress: 3.0% ... Training loss: 0.320 ... Validation loss: 0.505[[ 0.2607217 ]
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[[ 0.04959492 -0.12770709  0.02832963 ..., -0.1259915   0.15054715
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   0.20729374]]
Progress: 3.0% ... Training loss: 0.334 ... Validation loss: 0.518[[ 0.27793885]
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[[ 0.05060029 -0.12864854  0.02557795 ..., -0.12631922  0.15319061 -0.16577   ]
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   0.20568016]]
Progress: 3.0% ... Training loss: 0.325 ... Validation loss: 0.513[[ 0.26929016]
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[[ 0.05024946 -0.128372    0.02657998 ..., -0.12623756  0.15220333
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  -0.23293037]
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   0.20418672]]
Progress: 3.0% ... Training loss: 0.315 ... Validation loss: 0.499[[ 0.27348722]
 [-0.233898  ]
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 [ 0.39102703]
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[[ 0.05031991 -0.1284117   0.02658085 ..., -0.12625341  0.15250199
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   0.20516765]]
Progress: 3.0% ... Training loss: 0.316 ... Validation loss: 0.501[[ 0.27290304]
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[[ 0.05028438 -0.1284014   0.02669953 ..., -0.12623873  0.15232656
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   0.20599423]]
Progress: 3.0% ... Training loss: 0.315 ... Validation loss: 0.500[[ 0.26306594]
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[[ 0.04939844 -0.12758104  0.02938423 ..., -0.12598556  0.15004487
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 [ 0.06258991 -0.03631265 -0.07697178 ...,  0.03955199  0.20218197
   0.2065401 ]]
Progress: 3.0% ... Training loss: 0.326 ... Validation loss: 0.507[[ 0.27688231]
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[[ 0.04988998 -0.12806401  0.0278868  ..., -0.12613416  0.15136248
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 [ 0.06316525 -0.03684282 -0.0786924  ...,  0.03938133  0.20382473
   0.20495967]]
Progress: 3.0% ... Training loss: 0.319 ... Validation loss: 0.507[[ 0.26691308]
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[[ 0.0489286  -0.12723938  0.03078263 ..., -0.12590777  0.14872475
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 [ 0.06296252 -0.03666516 -0.0781209  ...,  0.03943385  0.20339241
   0.20545202]]
Progress: 3.0% ... Training loss: 0.320 ... Validation loss: 0.500[[ 0.28142536]
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[[ 0.04964008 -0.12791222  0.02877659 ..., -0.12612038  0.15058752
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   0.20403809]]
Progress: 3.1% ... Training loss: 0.325 ... Validation loss: 0.517[[ 0.27453048]
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[[ 0.0496135  -0.12789827  0.0291764  ..., -0.12611144  0.15035967
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 [ 0.06353229 -0.03720086 -0.07967947 ...,  0.03926259  0.20501712
   0.20383213]]
Progress: 3.1% ... Training loss: 0.315 ... Validation loss: 0.502[[ 0.26624738]
 [-0.24002934]
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[[ 0.0487331  -0.12714762  0.03173568 ..., -0.12587792  0.14811631
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   0.20405526]]
Progress: 3.1% ... Training loss: 0.324 ... Validation loss: 0.504[[ 0.2888665 ]
 [-0.22164432]
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[[ 0.05004993 -0.12839488  0.02790046 ..., -0.12630168  0.15179338
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 [-0.19339682 -0.17784766 -0.11429781 ...,  0.11027948 -0.04498255
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 [ 0.06390734 -0.03755748 -0.08080636 ...,  0.03913737  0.20631619
   0.20285444]]
Progress: 3.1% ... Training loss: 0.347 ... Validation loss: 0.534[[ 0.27166305]
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[[ 0.04860743 -0.12732801  0.03168861 ..., -0.12599897  0.14805586
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 [-0.19385408 -0.17749726 -0.11308064 ...,  0.11038135 -0.04619006
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  -0.23025177]
 [ 0.06359278 -0.03729555 -0.0799394  ...,  0.03920004  0.20552658
   0.20362997]]
Progress: 3.1% ... Training loss: 0.319 ... Validation loss: 0.494[[ 0.28382338]
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[[ 0.04879511 -0.12753395  0.03127789 ..., -0.12605957  0.14870283
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 [-0.19371903 -0.17760693 -0.11345332 ...,  0.11034231 -0.04588968
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   0.2025984 ]]
Progress: 3.1% ... Training loss: 0.319 ... Validation loss: 0.498[[ 0.27230961]
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[[ 0.04804657 -0.12694002  0.03329245 ..., -0.1258786   0.14696669
  -0.1596832 ]
 [ 0.03583881  0.05207232  0.1298929  ..., -0.2427     -0.05786745
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   0.20310353]]
Progress: 3.1% ... Training loss: 0.321 ... Validation loss: 0.495[[ 0.28917221]
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 [ 1.03191414]
 [ 0.40444911]
 [-0.64986288]
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 [ 0.1167798 ]
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[[ 0.04953111 -0.12830801  0.02892755 ..., -0.12633661  0.15113871
  -0.16349306]
 [ 0.03572663  0.05216874  0.1302207  ..., -0.24266736 -0.05813601
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 [-0.19418683 -0.1772352  -0.11220981 ...,  0.11044219 -0.04726272
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  -0.2300972 ]
 [ 0.0639839  -0.03767783 -0.08114947 ...,  0.03907631  0.2069231
   0.20252748]]
Progress: 3.1% ... Training loss: 0.328 ... Validation loss: 0.509[[ 0.27127025]
 [-0.24338912]
 [-0.78639532]
 [-0.79943296]
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 [ 1.01942406]
 [ 0.39043074]
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 [ 0.23464129]
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[[ 0.04866094 -0.1275756   0.03141339 ..., -0.1261207   0.1484523
  -0.16128274]
 [ 0.03555096  0.0523026   0.13067559 ..., -0.24262645 -0.05859916
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 [-0.19506778 -0.17653701 -0.10996035 ...,  0.11064133 -0.04961866
  -0.01389911]
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  -0.23048205]
 [ 0.0634196  -0.03721451 -0.07962345 ...,  0.03921103  0.20555424
   0.20394168]]
Progress: 3.1% ... Training loss: 0.325 ... Validation loss: 0.494[[ 0.28319351]
 [-0.23152953]
 [-0.77663982]
 [-0.78781857]
 [-0.23563673]
 [ 1.02831251]
 [ 0.39990372]
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[[ 0.04873287 -0.12764013  0.03120448 ..., -0.12614131  0.14874216
  -0.16154329]
 [ 0.03563188  0.05222978  0.13043933 ..., -0.24265064 -0.05838859
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 [-0.19516978 -0.17644533 -0.10964457 ...,  0.11067023 -0.04989082
  -0.01360203]
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  -0.23074264]
 [ 0.06373746 -0.03752772 -0.08056955 ...,  0.03910461  0.20646866
   0.20304919]]
Progress: 3.1% ... Training loss: 0.314 ... Validation loss: 0.493[[ 0.2863538 ]
 [-0.23174514]
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 [-0.78727814]
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 [ 1.03194577]
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[[ 0.04919605 -0.12805695  0.02996044 ..., -0.12626957  0.14989027
  -0.1627773 ]
 [ 0.03569518  0.05216842  0.13021594 ..., -0.24266694 -0.05816905
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 ..., 
 [-0.19497298 -0.17660463 -0.11009887 ...,  0.1106183  -0.04948574
  -0.01406836]
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  -0.23090929]
 [ 0.06387424 -0.037642   -0.08097079 ...,  0.0390714   0.20690577
   0.20276442]]
Progress: 3.1% ... Training loss: 0.318 ... Validation loss: 0.496[[ 0.28024206]
 [-0.23788529]
 [-0.77873827]
 [-0.79292968]
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 [ 1.02830568]
 [ 0.39563044]
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[[ 0.04876515 -0.12771655  0.03114152 ..., -0.1261778   0.14885556
  -0.16192588]
 [ 0.03542127  0.0523953   0.13093217 ..., -0.24260343 -0.05884222
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 [-0.19542917 -0.17623527 -0.1089304  ...,  0.11072893 -0.05068411
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  -0.23071073]
 [ 0.06437266 -0.03805888 -0.08232514 ...,  0.03894264  0.20835556
   0.20147162]]
Progress: 3.1% ... Training loss: 0.312 ... Validation loss: 0.487[[ 0.28183263]
 [-0.23664038]
 [-0.77752178]
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 [ 0.39690025]
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[[ 0.04826729 -0.12729023  0.0326442  ..., -0.12603824  0.14750967
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 [-0.19513982 -0.17648683 -0.10972185 ...,  0.11065979 -0.04996166
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  -0.23079507]
 [ 0.06435163 -0.0380426  -0.08227172 ...,  0.03895354  0.20841557
   0.20148414]]
Progress: 3.1% ... Training loss: 0.312 ... Validation loss: 0.488[[ 0.27949688]
 [-0.23875995]
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[[ 0.04792988 -0.12699523  0.03356939 ..., -0.12594991  0.1464697
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 [-0.19531338 -0.17634131 -0.10926278 ...,  0.11070378 -0.05043816
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  -0.23109691]
 [ 0.06389337 -0.03763911 -0.08101439 ...,  0.03907178  0.20720919
   0.20264424]]
Progress: 3.1% ... Training loss: 0.312 ... Validation loss: 0.490[[ 0.28837949]
 [-0.23140646]
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 [ 1.03166334]
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[[ 0.04800638 -0.12708102  0.03334438 ..., -0.12597163  0.14667176
  -0.16003192]
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   0.13539702]
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  -0.23108417]
 [ 0.06432351 -0.03800639 -0.08215403 ...,  0.03895436  0.2083631
   0.20156994]]
Progress: 3.1% ... Training loss: 0.319 ... Validation loss: 0.506[[ 0.27524386]
 [-0.24435166]
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 [ 1.02159837]
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[[ 0.04767144 -0.12682292  0.0342802  ..., -0.12588992  0.14585388
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 [-0.19506397 -0.17654796 -0.1099494  ...,  0.11064366 -0.04992562
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  -0.23099959]
 [ 0.06366119 -0.0374436  -0.08041939 ...,  0.03912637  0.20685765
   0.20325209]]
Progress: 3.2% ... Training loss: 0.322 ... Validation loss: 0.500[[ 0.27405029]
 [-0.24671103]
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[[  4.75824133e-02  -1.26758462e-01   3.45619521e-02 ...,  -1.25861147e-01
    1.45537275e-01  -1.59041187e-01]
 [  3.53045913e-02   5.24743189e-02   1.31149773e-01 ...,  -2.42579079e-01
   -5.90821549e-02   1.35718134e-01]
 [  5.49904199e-03  -5.88218957e-03  -1.60057102e-01 ...,   1.62687918e-01
    8.75058249e-02   1.42817580e-01]
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 [ -1.95200245e-01  -1.76436909e-01  -1.09572891e-01 ...,   1.10681322e-01
   -5.03733153e-02  -1.35252246e-02]
 [ -2.77297984e-01  -2.20148985e-01  -4.61895928e-02 ...,  -1.15165449e-01
   -2.75658790e-05  -2.31546796e-01]
 [  6.38551671e-02  -3.76203803e-02  -8.10033050e-02 ...,   3.90697415e-02
    2.07418691e-01   2.02729372e-01]]
Progress: 3.2% ... Training loss: 0.327 ... Validation loss: 0.503[[ 0.288644  ]
 [-0.23293587]
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[[ 0.04862161 -0.12771035  0.03175125 ..., -0.12618069  0.14826382
  -0.16178286]
 [ 0.03529111  0.05248652  0.13118703 ..., -0.2425748  -0.05910772
   0.13575478]
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 ..., 
 [-0.19532492 -0.17632048 -0.10921223 ...,  0.11071712 -0.0507011
  -0.01318796]
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  -0.23312695]
 [ 0.06386265 -0.03761244 -0.08096815 ...,  0.03906625  0.20746703
   0.20272514]]
Progress: 3.2% ... Training loss: 0.319 ... Validation loss: 0.506[[ 0.27367672]
 [-0.24631213]
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[[ 0.04787282 -0.12707538  0.03380946 ..., -0.12598729  0.14627512
  -0.15989362]
 [ 0.03517084  0.0525844   0.13151554 ..., -0.24254611 -0.05941434
   0.13600562]
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   0.14181319]
 ..., 
 [-0.19574502 -0.17598052 -0.10808552 ...,  0.11082115 -0.05180434
  -0.01216411]
 [-0.27653388 -0.22081973 -0.04815545 ..., -0.11538753  0.00190034
  -0.23346158]
 [ 0.06352126 -0.037324   -0.08002483 ...,  0.03915684  0.20655155
   0.20361503]]
Progress: 3.2% ... Training loss: 0.325 ... Validation loss: 0.503[[ 0.29366418]
 [-0.22935383]
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[[ 0.04949755 -0.12851657  0.02932727 ..., -0.12647545  0.15017151
  -0.16400749]
 [ 0.0354304   0.05234291  0.13074764 ..., -0.24262839 -0.05868969
   0.13528661]
 [ 0.00739231 -0.00765184 -0.16541436 ...,  0.16206196  0.09234849
   0.13788696]
 ..., 
 [-0.19486686 -0.17675126 -0.11056448 ...,  0.11054922 -0.04962543
  -0.01447828]
 [-0.27607072 -0.22122685 -0.04947292 ..., -0.11552519  0.00302982
  -0.23461703]
 [ 0.06349307 -0.03729744 -0.07992656 ...,  0.0391677   0.20647026
   0.20368394]]
Progress: 3.2% ... Training loss: 0.340 ... Validation loss: 0.526[[ 0.27075156]
 [-0.2511203 ]
 [-0.78689869]
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 [ 1.02458291]
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[[ 0.04805782 -0.12738553  0.03316283 ..., -0.12614468  0.14651071
  -0.16038544]
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   0.1350839 ]
 [ 0.00605689 -0.00665484 -0.1621871  ...,  0.16235891  0.08879019
   0.14125547]
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 [-0.19500308 -0.17665011 -0.11020479 ...,  0.11057809 -0.04995448
  -0.01414694]
 [-0.27659973 -0.22082185 -0.04811391 ..., -0.11540345  0.00167723
  -0.23335335]
 [ 0.06277183 -0.03673096 -0.07801542 ...,  0.0393414   0.20468387
   0.20549885]]
Progress: 3.2% ... Training loss: 0.335 ... Validation loss: 0.510[[ 0.29387366]
 [-0.23137072]
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 [ 1.04232401]
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[[ 0.04900233 -0.12829294  0.03039571 ..., -0.12645739  0.14901334
  -0.16291213]
 [ 0.03552751  0.05226999  0.1304836  ..., -0.24265272 -0.05844036
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   0.20403123]]
Progress: 3.2% ... Training loss: 0.331 ... Validation loss: 0.522[[ 0.2802087 ]
 [-0.24581039]
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 [ 0.39386792]
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[[  4.82412499e-02  -1.27708146e-01   3.24988440e-02 ...,  -1.26299658e-01
    1.47131137e-01  -1.61094794e-01]
 [  3.55747090e-02   5.22341282e-02   1.30364747e-01 ...,  -2.42662653e-01
   -5.83253738e-02   1.35011558e-01]
 [  5.98368228e-03  -6.49998407e-03  -1.61690346e-01 ...,   1.62430805e-01
    8.85184734e-02   1.41696188e-01]
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 [ -1.94220754e-01  -1.77384136e-01  -1.12419902e-01 ...,   1.10309558e-01
   -4.79475185e-02  -1.62225093e-02]
 [ -2.77241600e-01  -2.20370763e-01  -4.65359346e-02 ...,  -1.15289682e-01
    7.43036198e-05  -2.31981432e-01]
 [  6.32169232e-02  -3.71617406e-02  -7.93418299e-02 ...,   3.91945445e-02
    2.06191865e-01   2.04214970e-01]]
Progress: 3.2% ... Training loss: 0.314 ... Validation loss: 0.488[[ 0.29549801]
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[[ 0.04884401 -0.12822601  0.03093013 ..., -0.12647574  0.14875102
  -0.16245014]
 [ 0.03554402  0.05225916  0.13044525 ..., -0.24265312 -0.05840867
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  -0.2323586 ]
 [ 0.06351316 -0.03742342 -0.08019535 ...,  0.03910485  0.20701825
   0.20343314]]
Progress: 3.2% ... Training loss: 0.325 ... Validation loss: 0.508[[ 0.27842259]
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[[  4.71079587e-02  -1.26798826e-01   3.55919556e-02 ...,  -1.26072014e-01
    1.44288829e-01  -1.58142464e-01]
 [  3.55053741e-02   5.22898838e-02   1.30546039e-01 ...,  -2.42644492e-01
   -5.85114776e-02   1.35187382e-01]
 [  5.98357563e-03  -6.46075736e-03  -1.61493297e-01 ...,   1.62470303e-01
    8.86018091e-02   1.42115793e-01]
 ..., 
 [ -1.94344331e-01  -1.77313395e-01  -1.12038263e-01 ...,   1.10321983e-01
   -4.82622459e-02  -1.59196912e-02]
 [ -2.77377488e-01  -2.20271113e-01  -4.62262687e-02 ...,  -1.15273249e-01
   -2.14007634e-04  -2.31699900e-01]
 [  6.29832025e-02  -3.69866896e-02  -7.87647968e-02 ...,   3.92264189e-02
    2.05675352e-01   2.04746280e-01]]
Progress: 3.2% ... Training loss: 0.323 ... Validation loss: 0.494[[ 0.29480585]
 [-0.23785391]
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[[  4.83922222e-02  -1.27972915e-01   3.21538492e-02 ...,  -1.26449825e-01
    1.47626781e-01  -1.61603666e-01]
 [  3.53272353e-02   5.24522113e-02   1.31057186e-01 ...,  -2.42593375e-01
   -5.89755662e-02   1.35568171e-01]
 [  7.00528139e-03  -7.38795570e-03  -1.64080909e-01 ...,   1.62162131e-01
    9.07181181e-02   1.39596314e-01]
 ..., 
 [ -1.94042635e-01  -1.77594609e-01  -1.12843216e-01 ...,   1.10234873e-01
   -4.75015261e-02  -1.66582659e-02]
 [ -2.77352617e-01  -2.20297284e-01  -4.62856291e-02 ...,  -1.15281465e-01
   -1.44090563e-04  -2.31701361e-01]
 [  6.28905315e-02  -3.68913177e-02  -7.84526923e-02 ...,   3.92508077e-02
    2.05500648e-01   2.05001308e-01]]
Progress: 3.2% ... Training loss: 0.318 ... Validation loss: 0.493[[ 0.27513613]
 [-0.25561599]
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 [ 1.03075385]
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[[ 0.04737131 -0.12709784  0.03497686 ..., -0.12619011  0.14519594
  -0.15895653]
 [ 0.03497505  0.05273484  0.13196582 ..., -0.24251112 -0.05987644
   0.13637423]
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 [-0.19448635 -0.17723573 -0.11170088 ...,  0.11033212 -0.04859793
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  -0.23060443]
 [ 0.06205797 -0.03615656 -0.07614413 ...,  0.03945057  0.20350958
   0.20714179]]
Progress: 3.2% ... Training loss: 0.337 ... Validation loss: 0.507[[ 0.29986656]
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[[ 0.04868751 -0.12831216  0.03146018 ..., -0.12661252  0.14855431
  -0.16243651]
 [ 0.0351087   0.05260721  0.13157076 ..., -0.24255072 -0.05951926
   0.13600242]
 [ 0.00961985 -0.0099659  -0.17165235 ...,  0.16130405  0.09765794
   0.133055  ]
 ..., 
 [-0.19408699 -0.17760749 -0.11283138 ...,  0.110207   -0.04755461
  -0.01674483]
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  -0.23129685]
 [ 0.06298307 -0.03703664 -0.07874875 ...,  0.03914135  0.20610297
   0.20453521]]
Progress: 3.2% ... Training loss: 0.343 ... Validation loss: 0.510[[ 0.27489622]
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[[ 0.04699717 -0.12694449  0.03589789 ..., -0.12623759  0.14415589
  -0.15822702]
 [ 0.03522473  0.05251674  0.13127195 ..., -0.24257477 -0.05923324
   0.13572531]
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   0.13731529]
 ..., 
 [-0.19495638 -0.17693259 -0.11065409 ...,  0.11038415 -0.04977703
  -0.01468933]
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  -0.2301154 ]
 [ 0.0628802  -0.03695153 -0.07851204 ...,  0.0391615   0.20585253
   0.20474738]]
Progress: 3.2% ... Training loss: 0.331 ... Validation loss: 0.499[[ 0.28456311]
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[[ 0.04733032 -0.12727855  0.03495429 ..., -0.12633439  0.14514803
  -0.15913213]
 [ 0.03538417  0.05236973  0.13082846 ..., -0.24262206 -0.05879316
   0.13531379]
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   0.14166267]
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 [-0.19496428 -0.17692462 -0.11061684 ...,  0.11039063 -0.04981507
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  -0.2313337 ]
 [ 0.06320626 -0.03726739 -0.07948327 ...,  0.03906262  0.20670688
   0.20384463]]
Progress: 3.2% ... Training loss: 0.309 ... Validation loss: 0.483[[ 0.28626193]
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[[ 0.04726215 -0.12723407  0.0353095  ..., -0.12631361  0.14493362
  -0.15906393]
 [ 0.03541584  0.05234191  0.1307396  ..., -0.24263082 -0.05870449
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   0.14529065]
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 [-0.19485329 -0.17702246 -0.1108961  ...,  0.11035734 -0.04960759
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  -0.23138057]
 [ 0.06283623 -0.03693946 -0.07846251 ...,  0.03917052  0.20589707
   0.20480384]]
Progress: 3.3% ... Training loss: 0.310 ... Validation loss: 0.489[[ 0.28706174]
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[[ 0.04759458 -0.12747912  0.03450933 ..., -0.12640378  0.14565175
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 [-0.19476001 -0.17709806 -0.11114109 ...,  0.11032984 -0.0493619
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  -0.23179252]
 [ 0.06276829 -0.03687831 -0.07822785 ...,  0.03919625  0.20577964
   0.20499192]]
Progress: 3.3% ... Training loss: 0.309 ... Validation loss: 0.486[[ 0.27767303]
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[[ 0.04747629 -0.12735247  0.03487927 ..., -0.12637495  0.14512031
  -0.15915411]
 [ 0.03549946  0.0522726   0.13051609 ..., -0.24265264 -0.05849233
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 [-0.19520341 -0.17672821 -0.10993686 ...,  0.11043797 -0.05059562
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 [ 0.06270005 -0.03678945 -0.07805296 ...,  0.03922269  0.2057108
   0.20529053]]
Progress: 3.3% ... Training loss: 0.317 ... Validation loss: 0.487[[ 0.28346901]
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[[  4.75093822e-02  -1.27423531e-01   3.47277687e-02 ...,  -1.26392590e-01
    1.45331328e-01  -1.59204183e-01]
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   -5.83550657e-02   1.34923644e-01]
 [  3.83938777e-03  -5.22794882e-03  -1.56334568e-01 ...,   1.62779670e-01
    8.23976665e-02   1.47786960e-01]
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 [ -1.95299249e-01  -1.76640728e-01  -1.09667039e-01 ...,   1.10464052e-01
   -5.08540051e-02  -1.38196122e-02]
 [ -2.77220608e-01  -2.20520097e-01  -4.68263724e-02 ...,  -1.15411518e-01
    2.11950685e-04  -2.32165687e-01]
 [  6.25853980e-02  -3.66927851e-02  -7.77413125e-02 ...,   3.92640005e-02
    2.05605760e-01   2.05654893e-01]]
Progress: 3.3% ... Training loss: 0.309 ... Validation loss: 0.483[[ 0.28325073]
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[[  4.72323761e-02  -1.27187547e-01   3.55484779e-02 ...,  -1.26321215e-01
    1.44570946e-01  -1.58546920e-01]
 [  3.55765044e-02   5.22050739e-02   1.30297224e-01 ...,  -2.42673568e-01
   -5.82786501e-02   1.34845701e-01]
 [  3.57049059e-03  -5.03622022e-03  -1.55655614e-01 ...,   1.62840794e-01
    8.16479038e-02   1.48385404e-01]
 ..., 
 [ -1.95319138e-01  -1.76636347e-01  -1.09607523e-01 ...,   1.10468714e-01
   -5.09264105e-02  -1.38101122e-02]
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    7.24149591e-05  -2.32073368e-01]
 [  6.25275471e-02  -3.66271553e-02  -7.75651952e-02 ...,   3.92810608e-02
    2.05454493e-01   2.05775518e-01]]
Progress: 3.3% ... Training loss: 0.310 ... Validation loss: 0.484[[ 0.2882134 ]
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[[  4.71246836e-02  -1.27090297e-01   3.59505269e-02 ...,  -1.26276715e-01
    1.44223581e-01  -1.58207874e-01]
 [  3.57512399e-02   5.20426382e-02   1.29782259e-01 ...,  -2.42728114e-01
   -5.77672114e-02   1.34369859e-01]
 [  4.25904410e-03  -5.70579540e-03  -1.57685979e-01 ...,   1.62645932e-01
    8.34404242e-02   1.46479597e-01]
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   -5.08252977e-02  -1.39696057e-02]
 [ -2.77193512e-01  -2.20545161e-01  -4.69071349e-02 ...,  -1.15412873e-01
    1.59282930e-04  -2.32335640e-01]
 [  6.29647406e-02  -3.70221515e-02  -7.87868739e-02 ...,   3.91500722e-02
    2.06719061e-01   2.04614774e-01]]
Progress: 3.3% ... Training loss: 0.309 ... Validation loss: 0.486[[ 0.28523603]
 [-0.24580387]
 [-0.78368863]
 [-0.8002841 ]
 [-0.23949054]
 [ 1.04266946]
 [ 0.40322118]
 [-0.66313587]
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 [ 0.11563955]
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 [ 1.04888364]
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 [ 1.64166018]
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[[  4.68057806e-02  -1.26843968e-01   3.69632004e-02 ...,  -1.26206568e-01
    1.43408931e-01  -1.57524065e-01]
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   -5.77282395e-02   1.34339951e-01]
 [  4.19302157e-03  -5.66635250e-03  -1.57427874e-01 ...,   1.62663728e-01
    8.31841109e-02   1.46699743e-01]
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 [ -1.95346465e-01  -1.76634692e-01  -1.09512302e-01 ...,   1.10471793e-01
   -5.10082439e-02  -1.38667017e-02]
 [ -2.77251022e-01  -2.20497174e-01  -4.67636212e-02 ...,  -1.15400117e-01
    1.20347903e-05  -2.32190383e-01]
 [  6.29443579e-02  -3.69993591e-02  -7.87173158e-02 ...,   3.91643873e-02
    2.06692827e-01   2.04711305e-01]]
Progress: 3.3% ... Training loss: 0.308 ... Validation loss: 0.482[[ 0.29276625]
 [-0.24028938]
 [-0.77920706]
 [-0.79641367]
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 [ 1.04981702]
 [ 0.41004033]
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[[ 0.04760863 -0.12754471  0.03485548 ..., -0.12641375  0.14549615
  -0.15965722]
 [ 0.03580722  0.05198841  0.1295891  ..., -0.24274614 -0.05758996
   0.13420043]
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 [-0.1952639  -0.17669719 -0.10969395 ...,  0.11045199 -0.05081721
  -0.01402435]
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  -0.23265139]
 [ 0.06342453 -0.03743625 -0.08008152 ...,  0.03902477  0.20808583
   0.20341414]]
Progress: 3.3% ... Training loss: 0.315 ... Validation loss: 0.485[[ 0.27972507]
 [-0.25235815]
 [-0.78916595]
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 [ 1.03923085]
 [ 0.39953945]
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[[ 0.0468062  -0.1268924   0.03705356 ..., -0.12620891  0.14321088
  -0.15758928]
 [ 0.03572093  0.05205572  0.12982064 ..., -0.24272487 -0.05781864
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   0.14473452]
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 [-0.19556377 -0.17645494 -0.10895355 ...,  0.1105237  -0.05158553
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  -0.23294741]
 [ 0.06330066 -0.03734027 -0.079769   ...,  0.03903547  0.20777759
   0.20364569]]
Progress: 3.3% ... Training loss: 0.317 ... Validation loss: 0.485[[ 0.29165126]
 [-0.24237382]
 [-0.77984124]
 [-0.79812106]
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 [ 1.04737904]
 [ 0.40841526]
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[[ 0.0474373  -0.12750217  0.03525559 ..., -0.12640702  0.14497233
  -0.15939288]
 [ 0.03568049  0.0520918   0.12993798 ..., -0.24271427 -0.0579341
   0.13452323]
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 [-0.19541383 -0.17659823 -0.10937714 ...,  0.11047655 -0.05121533
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  -0.2332382 ]
 [ 0.06372772 -0.03773817 -0.08093884 ...,  0.03890718  0.20894413
   0.2024823 ]]
Progress: 3.3% ... Training loss: 0.311 ... Validation loss: 0.484[[ 0.28060512]
 [-0.25262526]
 [-0.78845969]
 [-0.80639041]
 [-0.24520063]
 [ 1.03757745]
 [ 0.39876589]
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[[ 0.04655228 -0.12674847  0.0376161  ..., -0.126179    0.14265057
  -0.15713257]
 [ 0.03549719  0.05223552  0.13043246 ..., -0.24266762 -0.05843984
   0.13497679]
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   0.14618226]
 ..., 
 [-0.19571149 -0.17635082 -0.10858804 ...,  0.11055039 -0.05196335
  -0.01300714]
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  -0.23344998]
 [ 0.0635344  -0.03755447 -0.0803791  ...,  0.03896214  0.20854201
   0.20306014]]
Progress: 3.3% ... Training loss: 0.316 ... Validation loss: 0.488[[ 0.3024906 ]
 [-0.23243703]
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 [ 1.05867478]
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[[ 0.04800794 -0.12808676  0.03360645 ..., -0.12660812  0.14649428
  -0.16094462]
 [ 0.03559395  0.05215108  0.13019113 ..., -0.24269581 -0.05818436
   0.13473536]
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   0.13977794]
 ..., 
 [-0.19523484 -0.17678464 -0.10993582 ...,  0.11040939 -0.05074522
  -0.01428118]
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  -0.23468598]
 [ 0.06340509 -0.03741029 -0.07991761 ...,  0.03900969  0.20840071
   0.20340748]]
Progress: 3.3% ... Training loss: 0.352 ... Validation loss: 0.521[[ 0.29123591]
 [-0.24236998]
 [-0.78011177]
 [-0.80072174]
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 [ 1.05385898]
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[[ 0.04811758 -0.12816392  0.03348421 ..., -0.12662732  0.14677656
  -0.16114674]
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   0.13544334]
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   0.13868423]
 ..., 
 [-0.19507829 -0.17689995 -0.11025047 ...,  0.11037263 -0.05047343
  -0.01463322]
 [-0.27637548 -0.22126164 -0.04902292 ..., -0.115644    0.00218115
  -0.23430352]
 [ 0.06284245 -0.03696682 -0.07841027 ...,  0.03913482  0.20718361
   0.20474329]]
Progress: 3.3% ... Training loss: 0.314 ... Validation loss: 0.478[[ 0.28587571]
 [-0.24754125]
 [-0.78426332]
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 [ 1.05011419]
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[[ 0.0475158  -0.1276372   0.03519372 ..., -0.12647515  0.14511175
  -0.1595991 ]
 [ 0.03524008  0.0524217   0.13108685 ..., -0.24262034 -0.05908962
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   0.13709916]
 ..., 
 [-0.19523618 -0.17676919 -0.10985402 ...,  0.11041196 -0.0508876
  -0.01423515]
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  -0.23498988]
 [ 0.06289571 -0.03701033 -0.07854795 ...,  0.03912181  0.2072996
   0.20458922]]
Progress: 3.3% ... Training loss: 0.309 ... Validation loss: 0.473[[ 0.29815386]
 [-0.23665614]
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 [ 1.05886398]
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[[ 0.04773817 -0.1278452   0.03460202 ..., -0.1265343   0.1457052
  -0.16012737]
 [ 0.03527883  0.05238634  0.13097757 ..., -0.24262918 -0.05898144
   0.13548314]
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   0.13719123]
 ..., 
 [-0.19502167 -0.17696218 -0.11044032 ...,  0.11035477 -0.05038567
  -0.01481604]
 [-0.27581748 -0.2217281  -0.05044491 ..., -0.11577599  0.00354527
  -0.23566181]
 [ 0.06326698 -0.03735746 -0.07962789 ...,  0.03902353  0.20833176
   0.20360995]]
Progress: 3.3% ... Training loss: 0.334 ... Validation loss: 0.494[[ 0.27779584]
 [-0.25540896]
 [-0.79129473]
 [-0.81403193]
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 [ 1.04182468]
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[[ 0.04638249 -0.12676369  0.0381692  ..., -0.12623825  0.14227279
  -0.15684325]
 [ 0.03528632  0.05237982  0.13095685 ..., -0.24263232 -0.05895197
   0.13546604]
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   0.13600413]
 ..., 
 [-0.19524185 -0.1767884  -0.10986284 ...,  0.11040497 -0.05098563
  -0.0142607 ]
 [-0.27646629 -0.22122639 -0.04878596 ..., -0.11563802  0.00181552
  -0.23418285]
 [ 0.06306484 -0.0371916  -0.07906779 ...,  0.03907103  0.20789887
   0.20412212]]
Progress: 3.4% ... Training loss: 0.324 ... Validation loss: 0.497[[ 0.28773874]
 [-0.24437704]
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[[ 0.04707929 -0.12737964  0.03632686 ..., -0.12642881  0.14401089
  -0.15860544]
 [ 0.03536157  0.05231433  0.13074405 ..., -0.24265373 -0.0587443
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 ..., 
 [-0.19494316 -0.1770661  -0.11065156 ...,  0.11031941 -0.05026026
  -0.0150776 ]
 [-0.27613687 -0.22152297 -0.04968934 ..., -0.11573076  0.00268279
  -0.23496441]
 [ 0.06309089 -0.03721025 -0.07917384 ...,  0.03906295  0.20806518
   0.20410607]]
Progress: 3.4% ... Training loss: 0.309 ... Validation loss: 0.477[[ 0.28869279]
 [-0.24537465]
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 [ 0.40427036]
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[[ 0.04746615 -0.12776053  0.03532659 ..., -0.1265399   0.14511058
  -0.1595398 ]
 [ 0.03529129  0.05237391  0.13093602 ..., -0.24263603 -0.05893104
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   0.13830324]
 ..., 
 [-0.19486893 -0.17713131 -0.11083189 ...,  0.11029834 -0.05007979
  -0.0152406 ]
 [-0.2764716  -0.22123939 -0.0487961  ..., -0.11564917  0.00184404
  -0.23412207]
 [ 0.06271532 -0.03689234 -0.07821091 ...,  0.03915554  0.20731484
   0.20507979]]
Progress: 3.4% ... Training loss: 0.309 ... Validation loss: 0.474[[ 0.28118357]
 [-0.25163831]
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[[ 0.04652365 -0.12696412  0.03790878 ..., -0.12630628  0.14271815
  -0.15729045]
 [ 0.03552165  0.05217677  0.13028881 ..., -0.24269193 -0.05831692
   0.13481767]
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   0.13846959]
 ..., 
 [-0.19545174 -0.17663623 -0.10929568 ...,  0.11043453 -0.05157618
  -0.01382491]
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  -0.2335228 ]
 [ 0.06270527 -0.03687948 -0.07820008 ...,  0.03915572  0.20750722
   0.20507081]]
Progress: 3.4% ... Training loss: 0.314 ... Validation loss: 0.487[[ 0.29113617]
 [-0.24341892]
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[[ 0.04692725 -0.12732231  0.03691754 ..., -0.12642642  0.14361142
  -0.15838094]
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   0.20410242]]
Progress: 3.4% ... Training loss: 0.310 ... Validation loss: 0.477[[ 0.28399944]
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 [ 1.04365568]
 [ 0.40019896]
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[[ 0.04641423 -0.12688752  0.03829475 ..., -0.12629502  0.14232177
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   0.20459961]]
Progress: 3.4% ... Training loss: 0.310 ... Validation loss: 0.483[[ 0.28597804]
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[[ 0.04633686 -0.12682857  0.0385138  ..., -0.12627622  0.14209434
  -0.15696798]
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  -0.23361541]
 [ 0.06273126 -0.03690986 -0.0782172  ...,  0.03914477  0.20762048
   0.2049395 ]]
Progress: 3.4% ... Training loss: 0.308 ... Validation loss: 0.484[[ 0.29789763]
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 [ 1.05434045]
 [ 0.41166549]
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[[ 0.04682474 -0.12724241  0.03740105 ..., -0.12638945  0.14329199
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 [-0.19551568 -0.17658637 -0.1091106  ...,  0.11044126 -0.0518711
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  -0.23322005]
 [ 0.06321492 -0.03731778 -0.07953463 ...,  0.03902124  0.20891693
   0.20370287]]
Progress: 3.4% ... Training loss: 0.326 ... Validation loss: 0.493[[ 0.29205754]
 [-0.24108785]
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 [ 0.40634559]
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[[ 0.0465757  -0.12705189  0.0380617  ..., -0.1263427   0.14242497
  -0.15733334]
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  -0.23303603]
 [ 0.06294492 -0.0370897  -0.07881418 ...,  0.0390849   0.20828929
   0.20439247]]
Progress: 3.4% ... Training loss: 0.309 ... Validation loss: 0.482[[ 0.28984455]
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[[ 0.0459659  -0.1265342   0.03974663 ..., -0.12618134  0.14085805
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 [-0.19600068 -0.17620251 -0.10783444 ...,  0.1105437  -0.0531389
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  -0.23284809]
 [ 0.0635782  -0.03762097 -0.08054576 ...,  0.03892889  0.2099763
   0.20281188]]
Progress: 3.4% ... Training loss: 0.308 ... Validation loss: 0.484[[ 0.29829776]
 [-0.23701152]
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[[ 0.04677913 -0.12722651  0.03767667 ..., -0.12639338  0.14279742
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   0.20175634]]
Progress: 3.4% ... Training loss: 0.323 ... Validation loss: 0.497[[ 0.2982417 ]
 [-0.23904538]
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[[ 0.04659122 -0.12709974  0.03831048 ..., -0.12636581  0.14227545
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  -0.23289232]
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   0.19964185]]
Progress: 3.4% ... Training loss: 0.318 ... Validation loss: 0.487[[ 0.2895681 ]
 [-0.24655061]
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[[ 0.04672015 -0.12721676  0.03798962 ..., -0.12639082  0.14238751
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  -0.23300448]
 [ 0.06425557 -0.0381759  -0.08224114 ...,  0.03875722  0.21197468
   0.20108616]]
Progress: 3.4% ... Training loss: 0.307 ... Validation loss: 0.479[[ 0.30126893]
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[[ 0.04819171 -0.12849712  0.03414327 ..., -0.12679649  0.14606453
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 ..., 
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  -0.23308815]
 [ 0.06464705 -0.03851241 -0.08328569 ...,  0.03865184  0.21298967
   0.20009601]]
Progress: 3.4% ... Training loss: 0.327 ... Validation loss: 0.492[[ 0.28846424]
 [-0.25058702]
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[[  4.79826282e-02  -1.28337075e-01   3.47088448e-02 ...,  -1.26742689e-01
    1.45534529e-01  -1.60757972e-01]
 [  3.52799212e-02   5.23994160e-02   1.30917133e-01 ...,  -2.42630464e-01
   -5.89508398e-02   1.35455803e-01]
 [  4.12404959e-03  -6.37145195e-03  -1.57304294e-01 ...,   1.62396676e-01
    8.29855264e-02   1.46437393e-01]
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 [ -1.95828321e-01  -1.76334302e-01  -1.08205222e-01 ...,   1.10486337e-01
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 [ -2.77147601e-01  -2.20693844e-01  -4.69799220e-02 ...,  -1.15488524e-01
   -2.31369011e-04  -2.32473422e-01]
 [  6.39840302e-02  -3.79631700e-02  -8.14939753e-02 ...,   3.88069039e-02
    2.11387615e-01   2.01787692e-01]]
Progress: 3.4% ... Training loss: 0.307 ... Validation loss: 0.476[[ 0.3011088 ]
 [-0.24035489]
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[[ 0.0487436  -0.12901675  0.03263154 ..., -0.12695051  0.14751606
  -0.16256687]
 [ 0.03533544  0.05235128  0.13076914 ..., -0.24264563 -0.05880514
   0.13531601]
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   0.14777214]
 ..., 
 [-0.1957765  -0.17637746 -0.10833303 ...,  0.11047145 -0.05261953
  -0.01316567]
 [-0.2772498  -0.22060136 -0.046721   ..., -0.1154584  -0.00050799
  -0.23219483]
 [ 0.06436576 -0.03828915 -0.08251514 ...,  0.03870626  0.21251803
   0.20081845]]
Progress: 3.5% ... Training loss: 0.325 ... Validation loss: 0.489[[ 0.28016244]
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[[ 0.04752387 -0.12800341  0.03590858 ..., -0.12666777  0.14414233
  -0.15961549]
 [ 0.03518842  0.0524679   0.13115228 ..., -0.2426121  -0.05918898
   0.13564721]
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   0.15075505]
 ..., 
 [-0.19641473 -0.17586851 -0.10668895 ...,  0.11061419 -0.05427416
  -0.01166227]
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  -0.23167592]
 [ 0.06385118 -0.03785967 -0.08114234 ...,  0.03882971  0.21134696
   0.20209255]]
Progress: 3.5% ... Training loss: 0.330 ... Validation loss: 0.502[[ 0.29386825]
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[[ 0.04844264 -0.12886486  0.03344245 ..., -0.12696076  0.1466365
  -0.16190734]
 [ 0.03522599  0.05243365  0.13104453 ..., -0.24262387 -0.05908811
   0.13555594]
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 ..., 
 [-0.19574249 -0.17648575 -0.10846254 ...,  0.11040537 -0.05248742
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  -0.23191117]
 [ 0.06423271 -0.03820605 -0.08216651 ...,  0.03871613  0.21241553
   0.20111112]]
Progress: 3.5% ... Training loss: 0.310 ... Validation loss: 0.483[[ 0.28395443]
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[[ 0.04739339 -0.12797114  0.03627294 ..., -0.12670002  0.14380669
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 [-0.19591765 -0.17634295 -0.107997   ...,  0.11044843 -0.05297744
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  -0.23146844]
 [ 0.06438121 -0.03833486 -0.08256873 ...,  0.0386829   0.2128705
   0.20068818]]
Progress: 3.5% ... Training loss: 0.314 ... Validation loss: 0.487[[ 0.29942974]
 [-0.24050438]
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 [-0.80151926]
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 [ 1.05661984]
 [ 0.41383294]
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[[ 0.04848382 -0.12895     0.03334881 ..., -0.12701676  0.14680029
  -0.16203231]
 [ 0.03501111  0.05262357  0.13158558 ..., -0.24257193 -0.05957163
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 [-0.19546411 -0.17674153 -0.10913047 ...,  0.11031945 -0.05190093
  -0.01412354]
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  -0.23160441]
 [ 0.06485972 -0.03874436 -0.08387848 ...,  0.03855555  0.21415507
   0.19951058]]
Progress: 3.5% ... Training loss: 0.323 ... Validation loss: 0.499[[ 0.28459123]
 [-0.25514679]
 [-0.79475024]
 [-0.81582594]
 [-0.24883668]
 [ 1.04446133]
 [ 0.40094889]
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[[ 0.04719207 -0.12793871  0.03662988 ..., -0.12674034  0.14354736
  -0.15906829]
 [ 0.03494564  0.05267548  0.13175149 ..., -0.2425566  -0.05974984
   0.13631209]
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 [-0.19562935 -0.17660723 -0.10868902 ...,  0.11035551 -0.05234466
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 [-0.27808946 -0.21994971 -0.04449416 ..., -0.11528074 -0.00272058
  -0.23023437]
 [ 0.06467428 -0.03859112 -0.08336585 ...,  0.03859276  0.21369451
   0.19989918]]
Progress: 3.5% ... Training loss: 0.316 ... Validation loss: 0.487[[ 0.30271713]
 [-0.24009079]
 [-0.78048185]
 [-0.80101559]
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 [ 1.06231298]
 [ 0.41696479]
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[[ 0.04851667 -0.12913248  0.03300264 ..., -0.12712406  0.14708009
  -0.16234517]
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  -0.23220225]
 [ 0.06494112 -0.0388267  -0.08411007 ...,  0.03851871  0.21452063
   0.19922996]]
Progress: 3.5% ... Training loss: 0.328 ... Validation loss: 0.498[[ 0.28157342]
 [-0.25966712]
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 [-0.82029257]
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[[ 0.04679676 -0.12773583  0.03747111 ..., -0.12675668  0.14258183
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 [-0.19613206 -0.17620109 -0.10734856 ...,  0.110475   -0.05368535
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  -0.23178778]
 [ 0.06464928 -0.03857713 -0.08331653 ...,  0.03858596  0.21383989
   0.1999869 ]]
Progress: 3.5% ... Training loss: 0.329 ... Validation loss: 0.501[[ 0.30186927]
 [-0.2408893 ]
 [-0.78264446]
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 [ 1.06190912]
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[[ 0.04792954 -0.12881107  0.03428244 ..., -0.12710705  0.14556673
  -0.16125046]
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   0.13574788]
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 [-0.19557171 -0.17672837 -0.10890823 ...,  0.11031048 -0.05229785
  -0.0140535 ]
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  -0.23155007]
 [ 0.06487678 -0.03878881 -0.08397889 ...,  0.03851571  0.21446323
   0.19933215]]
Progress: 3.5% ... Training loss: 0.320 ... Validation loss: 0.486[[ 0.28844864]
 [-0.25200641]
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 [ 1.05024731]
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[[ 0.04718888 -0.12820406  0.03624784 ..., -0.12693964  0.14353305
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   0.13549408]
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 [-0.19616986 -0.17625517 -0.10737834 ...,  0.11044084 -0.05380242
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  -0.23140446]
 [ 0.06439387 -0.03840359 -0.08274328 ...,  0.03863116  0.21329478
   0.20055131]]
Progress: 3.5% ... Training loss: 0.310 ... Validation loss: 0.484[[ 0.28772652]
 [-0.25157277]
 [-0.79248757]
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[[  4.70540319e-02  -1.28076814e-01   3.66651450e-02 ...,  -1.26904891e-01
    1.43116791e-01  -1.58940596e-01]
 [  3.51788281e-02   5.24866457e-02   1.31149105e-01 ...,  -2.42612077e-01
   -5.91253081e-02   1.35649215e-01]
 [ -3.26301216e-05  -3.16287251e-03  -1.46408216e-01 ...,   1.63275373e-01
    7.19456394e-02   1.57920055e-01]
 ..., 
 [ -1.96299121e-01  -1.76141389e-01  -1.07098396e-01 ...,   1.10474932e-01
   -5.41559268e-02  -1.22695897e-02]
 [ -2.77537296e-01  -2.20440032e-01  -4.59426385e-02 ...,  -1.15467720e-01
   -1.36597734e-03  -2.31502158e-01]
 [  6.42275082e-02  -3.82436033e-02  -8.22818743e-02 ...,   3.86806885e-02
    2.12934586e-01   2.00986027e-01]]
Progress: 3.5% ... Training loss: 0.312 ... Validation loss: 0.487[[ 0.2995454 ]
 [-0.2417303 ]
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[[ 0.04817913 -0.1290959   0.03380294 ..., -0.12725469  0.146191
  -0.16182059]
 [ 0.03518607  0.05247857  0.13112535 ..., -0.24261437 -0.05910054
   0.13562985]
 [ 0.00085107 -0.00401349 -0.1486813  ...,  0.16298313  0.07450847
   0.15532198]
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 [-0.19641334 -0.17604923 -0.10682449 ...,  0.11050465 -0.05442966
  -0.01194816]
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  -0.23184902]
 [ 0.06481518 -0.03878771 -0.0839333  ...,  0.03849948  0.21469495
   0.19938682]]
Progress: 3.5% ... Training loss: 0.315 ... Validation loss: 0.485[[ 0.2807036 ]
 [-0.26057941]
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[[  4.72338495e-02  -1.28298268e-01   3.63240578e-02 ...,  -1.27015018e-01
    1.43676308e-01  -1.59316857e-01]
 [  3.52039442e-02   5.24642535e-02   1.31075670e-01 ...,  -2.42618378e-01
   -5.90535072e-02   1.35581657e-01]
 [  1.10576427e-04  -3.43970248e-03  -1.46871440e-01 ...,   1.63159701e-01
    7.26045063e-02   1.57343581e-01]
 ..., 
 [ -1.96734540e-01  -1.75777705e-01  -1.05999110e-01 ...,   1.10583724e-01
   -5.53492032e-02  -1.10867744e-02]
 [ -2.77812882e-01  -2.20232959e-01  -4.52386427e-02 ...,  -1.15410956e-01
   -2.05372243e-03  -2.30761199e-01]
 [  6.44099322e-02  -3.84537795e-02  -8.28330864e-02 ...,   3.85968642e-02
    2.13648654e-01   2.00388746e-01]]
Progress: 3.5% ... Training loss: 0.335 ... Validation loss: 0.508[[ 0.30968589]
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[[ 0.04947633 -0.13043175  0.03002439 ..., -0.12772206  0.1497801
  -0.16511589]
 [ 0.03540048  0.05227162  0.13048824 ..., -0.24268521 -0.05845621
   0.13500378]
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   0.15305797]
 ..., 
 [-0.19661739 -0.17588015 -0.10633053 ...,  0.11054862 -0.05503803
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  -0.23234537]
 [ 0.06499048 -0.03901452 -0.08445109 ...,  0.03840177  0.21529468
   0.1987526 ]]
Progress: 3.5% ... Training loss: 0.359 ... Validation loss: 0.523[[ 0.27574202]
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[[ 0.04761507 -0.12895892  0.03492295 ..., -0.12733974  0.14491935
  -0.16080354]
 [ 0.03523739  0.05239739  0.13090846 ..., -0.24265022 -0.05887093
   0.13532144]
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 [-0.19707509 -0.1755297  -0.10516738 ...,  0.11063919 -0.05622339
  -0.01034636]
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  -0.23137561]
 [ 0.0639298  -0.03817463 -0.08172506 ...,  0.0386237   0.2126661
   0.20130775]]
Progress: 3.5% ... Training loss: 0.354 ... Validation loss: 0.527[[ 0.30758957]
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[[  4.94958211e-02  -1.30776990e-01   2.95166153e-02 ...,  -1.27964745e-01
    1.49888220e-01  -1.65644396e-01]
 [  3.56203180e-02   5.20281350e-02   1.29811754e-01 ...,  -2.42780396e-01
   -5.78055788e-02   1.34266058e-01]
 [  1.72191592e-03  -5.13181689e-03  -1.51698916e-01 ...,   1.62528450e-01
    7.68333523e-02   1.53105878e-01]
 ..., 
 [ -1.96700590e-01  -1.75876717e-01  -1.06247754e-01 ...,   1.10511474e-01
   -5.52346236e-02  -1.12979245e-02]
 [ -2.77052107e-01  -2.21032231e-01  -4.75280486e-02 ...,  -1.15690032e-01
   -7.87028311e-05  -2.32903689e-01]
 [  6.41856295e-02  -3.84214264e-02  -8.24176761e-02 ...,   3.85422666e-02
    2.13521613e-01   2.00631563e-01]]
Progress: 3.6% ... Training loss: 0.353 ... Validation loss: 0.514[[ 0.28984645]
 [-0.25034689]
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[[ 0.04833525 -0.12984432  0.03274604 ..., -0.12772112  0.14673462
  -0.16294162]
 [ 0.03559836  0.05204781  0.12986424 ..., -0.24277621 -0.05782947
   0.1343557 ]
 [ 0.00160963 -0.00508797 -0.151327   ...,  0.1625338   0.07644392
   0.15359854]
 ..., 
 [-0.1969619  -0.1756841  -0.10557781 ...,  0.11056398 -0.05598479
  -0.01072027]
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  -0.23248363]
 [ 0.06355354 -0.03792505 -0.08075756 ...,  0.03867247  0.21204525
   0.20209635]]
Progress: 3.6% ... Training loss: 0.306 ... Validation loss: 0.476[[ 0.28966673]
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[[  4.80699833e-02  -1.29626230e-01   3.35643243e-02 ...,  -1.27663410e-01
    1.46167975e-01  -1.62261228e-01]
 [  3.56225946e-02   5.20290353e-02   1.29806032e-01 ...,  -2.42782590e-01
   -5.77581351e-02   1.34276262e-01]
 [  2.02212210e-03  -5.51002319e-03  -1.52538849e-01 ...,   1.62400447e-01
    7.72640427e-02   1.52448015e-01]
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   -5.54256497e-02  -1.13065017e-02]
 [ -2.76969638e-01  -2.21119309e-01  -4.77864627e-02 ...,  -1.15723392e-01
    8.58203321e-05  -2.33196257e-01]
 [  6.33230066e-02  -3.77019849e-02  -8.00801154e-02 ...,   3.87377182e-02
    2.11665208e-01   2.02755141e-01]]
Progress: 3.6% ... Training loss: 0.306 ... Validation loss: 0.476[[ 0.29447062]
 [-0.24754534]
 [-0.7903374 ]
 [-0.81529255]
 [-0.23784988]
 [ 1.06260428]
 [ 0.41382999]
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[[ 0.04792191 -0.12948746  0.03404737 ..., -0.12762371  0.14576604
  -0.16186007]
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   0.13438572]
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 [-0.19634919 -0.1762089  -0.1071301  ...,  0.11039505 -0.05449753
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  -0.23374267]
 [ 0.06355899 -0.03792591 -0.08074106 ...,  0.03866909  0.21242287
   0.20209718]]
Progress: 3.6% ... Training loss: 0.307 ... Validation loss: 0.473[[ 0.29114192]
 [-0.25198242]
 [-0.79505911]
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 [ 1.0607513 ]
 [ 0.41100685]
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[[ 0.04789257 -0.12950114  0.03422029 ..., -0.12762645  0.14574381
  -0.16180862]
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  -0.23355699]
 [ 0.06358287 -0.03794294 -0.08082128 ...,  0.03866184  0.21254156
   0.2020728 ]]
Progress: 3.6% ... Training loss: 0.306 ... Validation loss: 0.472[[ 0.29126533]
 [-0.25086015]
 [-0.79447872]
 [-0.81909236]
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 [ 1.06295752]
 [ 0.41100738]
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 [ 0.03276509]
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[[  4.79610789e-02  -1.29585503e-01   3.40146591e-02 ...,  -1.27637469e-01
    1.45955601e-01  -1.62015609e-01]
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   -5.68642078e-02   1.33400589e-01]
 [  2.37736839e-03  -5.99518339e-03  -1.53462349e-01 ...,   1.62248204e-01
    7.81013231e-02   1.51365658e-01]
 ..., 
 [ -1.96988527e-01  -1.75676867e-01  -1.05432847e-01 ...,   1.10550188e-01
   -5.62514143e-02  -1.06295068e-02]
 [ -2.76942673e-01  -2.21134903e-01  -4.78146917e-02 ...,  -1.15735104e-01
    1.51990189e-04  -2.33261763e-01]
 [  6.34763325e-02  -3.78312443e-02  -8.05444922e-02 ...,   3.86950582e-02
    2.12302483e-01   2.02389447e-01]]
Progress: 3.6% ... Training loss: 0.306 ... Validation loss: 0.471[[ 0.28636147]
 [-0.25548707]
 [-0.79756373]
 [-0.82318342]
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 [ 1.0576564 ]
 [ 0.40684735]
 [-0.68069061]
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[[ 0.04749312 -0.12918204  0.03534915 ..., -0.12751083  0.14481568
  -0.16086128]
 [ 0.03600731  0.05170082  0.12874803 ..., -0.24288649 -0.05671476
   0.13325445]
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 [-0.19683433 -0.17581139 -0.10583496 ...,  0.11050268 -0.05582329
  -0.01102909]
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  -0.23277741]
 [ 0.06381124 -0.03812527 -0.08145713 ...,  0.0385966   0.21321865
   0.20148038]]
Progress: 3.6% ... Training loss: 0.311 ... Validation loss: 0.481[[ 0.29163144]
 [-0.25038679]
 [-0.79361954]
 [-0.81840532]
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 [ 1.06291454]
 [ 0.41091736]
 [-0.67502518]
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[[ 0.04797667 -0.12962443  0.03411028 ..., -0.12764895  0.14608425
  -0.16212595]
 [ 0.03599798  0.05170919  0.12877231 ..., -0.24288367 -0.05674056
   0.13327925]
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 [-0.19690423 -0.17575031 -0.10565044 ...,  0.11052197 -0.05597209
  -0.01084818]
 [-0.27669451 -0.22135349 -0.048467   ..., -0.11580109  0.00078297
  -0.23393339]
 [ 0.0641107  -0.03838804 -0.08228172 ...,  0.03850926  0.2140614
   0.2007063 ]]
Progress: 3.6% ... Training loss: 0.305 ... Validation loss: 0.475[[ 0.28798447]
 [-0.25328672]
 [-0.79596324]
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 [ 1.06132708]
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[[ 0.04794416 -0.12956431  0.03431816 ..., -0.12762922  0.14584686
  -0.16181767]
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   0.13341971]
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   0.15572693]
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 [-0.19660335 -0.17602699 -0.10647238 ...,  0.11043331 -0.05522353
  -0.01153561]
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  -0.23444014]
 [ 0.06438621 -0.03861639 -0.08302973 ...,  0.03843615  0.21480598
   0.20007642]]
Progress: 3.6% ... Training loss: 0.307 ... Validation loss: 0.479[[ 0.30335528]
 [-0.24141768]
 [-0.78521035]
 [-0.81075334]
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 [ 1.07389649]
 [ 0.42255321]
 [-0.66617173]
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[[ 0.04871126 -0.1302239   0.03237913 ..., -0.12785244  0.14780588
  -0.1635477 ]
 [ 0.03588917  0.05180308  0.12902368 ..., -0.24285277 -0.05694535
   0.13355435]
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   0.15484186]
 ..., 
 [-0.19576282 -0.17675308 -0.10866641 ...,  0.11019377 -0.05311226
  -0.01362767]
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  -0.23442304]
 [ 0.06497558 -0.03913361 -0.08463829 ...,  0.03826893  0.21638257
   0.19856535]]
Progress: 3.6% ... Training loss: 0.329 ... Validation loss: 0.490[[ 0.29156367]
 [-0.25167114]
 [-0.79448952]
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 [ 1.06651465]
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[[ 0.04830728 -0.12988239  0.03356613 ..., -0.12775253  0.1465589
  -0.16240659]
 [ 0.03579123  0.05188215  0.12928032 ..., -0.24283075 -0.05720897
   0.13377249]
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   0.15467476]
 ..., 
 [-0.19596445 -0.17659922 -0.10819719 ...,  0.11023561 -0.05365371
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  -0.23434128]
 [ 0.06479733 -0.03897925 -0.08413116 ...,  0.03831086  0.21585986
   0.19903539]]
Progress: 3.6% ... Training loss: 0.305 ... Validation loss: 0.472[[ 0.28921438]
 [-0.25364521]
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[[ 0.04817964 -0.12975647  0.03399639 ..., -0.12772287  0.14613462
  -0.16214865]
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   0.13397548]
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 [-0.19550959 -0.1769842  -0.10936656 ...,  0.11011022 -0.05245322
  -0.01431655]
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  -0.23398871]
 [ 0.06482673 -0.03899284 -0.08423852 ...,  0.03830241  0.21596008
   0.19895985]]
Progress: 3.6% ... Training loss: 0.307 ... Validation loss: 0.473[[ 0.29076894]
 [-0.25040039]
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[[ 0.04842758 -0.12994155  0.03355453 ..., -0.12777211  0.14652084
  -0.16252517]
 [ 0.03577738  0.05189227  0.1293142  ..., -0.24282505 -0.05724762
   0.1338378 ]
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 [-0.19555919 -0.17693834 -0.10922556 ...,  0.11012472 -0.05257148
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  -0.23439028]
 [ 0.06459331 -0.03877775 -0.0835951  ...,  0.03837265  0.21552155
   0.1996156 ]]
Progress: 3.6% ... Training loss: 0.305 ... Validation loss: 0.468[[ 0.29768588]
 [-0.24436227]
 [-0.78880577]
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[[ 0.04932568 -0.13067855  0.0313723  ..., -0.1280186   0.14865452
  -0.16463406]
 [ 0.03591506  0.05177091  0.128949   ..., -0.24286453 -0.05686718
   0.13349617]
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   0.15078056]
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 [-0.19494958 -0.17745563 -0.11074209 ...,  0.1099508  -0.05114017
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 [-0.27615702 -0.22178749 -0.04975007 ..., -0.11595266  0.00200733
  -0.2350388 ]
 [ 0.06443437 -0.0386174  -0.08310226 ...,  0.03842405  0.21525592
   0.20011388]]
Progress: 3.6% ... Training loss: 0.319 ... Validation loss: 0.470[[ 0.28308871]
 [-0.25877901]
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[[ 0.04896512 -0.13041132  0.03245986 ..., -0.12794052  0.14788214
  -0.16394176]
 [ 0.03547367  0.05212944  0.13002798 ..., -0.24275658 -0.05794837
   0.13460282]
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   0.15326317]
 ..., 
 [-0.19529137 -0.17717449 -0.10986298 ...,  0.11003626 -0.05202091
  -0.01481901]
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  -0.23393502]
 [ 0.06410249 -0.03833385 -0.08220611 ...,  0.03850635  0.21445053
   0.20099267]]
Progress: 3.6% ... Training loss: 0.317 ... Validation loss: 0.485[[ 0.29132453]
 [-0.24970026]
 [-0.79586022]
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 [ 1.07176575]
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[[ 0.04931942 -0.13073528  0.03155019 ..., -0.12804773  0.14885143
  -0.16466296]
 [ 0.03538595  0.05220968  0.13027    ..., -0.24273017 -0.05817697
   0.13483722]
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   0.15528267]
 ..., 
 [-0.19510632 -0.1773362  -0.11040734 ...,  0.10997947 -0.05153122
  -0.01529141]
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  -0.23358102]
 [ 0.064099   -0.03831776 -0.08219104 ...,  0.03850908  0.21442511
   0.20103131]]
Progress: 3.7% ... Training loss: 0.305 ... Validation loss: 0.467[[ 0.28436175]
 [-0.25523896]
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[[  4.90080812e-02  -1.30421724e-01   3.26763210e-02 ...,  -1.27957324e-01
    1.48014867e-01  -1.63715517e-01]
 [  3.53325202e-02   5.22568663e-02   1.30419701e-01 ...,  -2.42715012e-01
   -5.83028772e-02   1.34911789e-01]
 [  1.90003763e-03  -5.59744021e-03  -1.50909692e-01 ...,   1.62295641e-01
    7.67216296e-02   1.53768383e-01]
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 [ -1.95332207e-01  -1.77142425e-01  -1.09739802e-01 ...,   1.10045945e-01
   -5.21748341e-02  -1.47190068e-02]
 [ -2.76900171e-01  -2.21159442e-01  -4.76745561e-02 ...,  -1.15767126e-01
    5.50537155e-06  -2.33268860e-01]
 [  6.38307854e-02  -3.80483354e-02  -8.13892178e-02 ...,   3.85907442e-02
    2.13820304e-01   2.01722448e-01]]
Progress: 3.7% ... Training loss: 0.311 ... Validation loss: 0.477[[ 0.30229112]
 [-0.24051467]
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 [-0.81376622]
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 [ 1.08172852]
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[[ 0.04992618 -0.13126165  0.03038997 ..., -0.12823283  0.15037683
  -0.16606934]
 [ 0.03530757  0.05228004  0.1304864  ..., -0.24270864 -0.05834924
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  -0.23293112]
 [ 0.06406681 -0.03826663 -0.08204739 ...,  0.03851944  0.21450747
   0.20107538]]
Progress: 3.7% ... Training loss: 0.329 ... Validation loss: 0.480[[ 0.28194156]
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 [ 1.06689415]
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[[ 0.04900462 -0.13049915  0.03301291 ..., -0.1280052   0.14792109
  -0.16368191]
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  -0.23172175]
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   0.20179709]]
Progress: 3.7% ... Training loss: 0.321 ... Validation loss: 0.486[[ 0.29733566]
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 [ 1.08005804]
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[[ 0.04935254 -0.13083205  0.03214002 ..., -0.12811792  0.14875542
  -0.1646604 ]
 [ 0.03529138  0.05229243  0.13053563 ..., -0.24270684 -0.05837815
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  -0.23236883]
 [ 0.0639613  -0.03818549 -0.08173655 ...,  0.03853199  0.21429679
   0.20130301]]
Progress: 3.7% ... Training loss: 0.311 ... Validation loss: 0.468[[ 0.29979219]
 [-0.24466297]
 [-0.79450534]
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 [ 1.08472743]
 [ 0.42326985]
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[[ 0.04951982 -0.13093864  0.03191156 ..., -0.12816322  0.14897605
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   0.13485047]
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 [-0.19493825 -0.1775129  -0.1106718  ...,  0.10990507 -0.05132141
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  -0.232848  ]
 [ 0.06388361 -0.03811709 -0.08150234 ...,  0.03855208  0.21413233
   0.20150575]]
Progress: 3.7% ... Training loss: 0.317 ... Validation loss: 0.472[[ 0.28470534]
 [-0.25893714]
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 [ 1.07291778]
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[[ 0.04851296 -0.13011238  0.03465235 ..., -0.12791685  0.14615868
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 [ 0.03531136  0.05225641  0.13045713 ..., -0.24271523 -0.05829819
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 [-0.19475239 -0.17766509 -0.11112991 ...,  0.10985802 -0.05095095
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  -0.23145249]
 [ 0.06315973 -0.03748492 -0.07950238 ...,  0.03873945  0.21236124
   0.20340424]]
Progress: 3.7% ... Training loss: 0.314 ... Validation loss: 0.479[[ 0.2869674 ]
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[[  4.82099628e-02  -1.29817054e-01   3.56826007e-02 ...,  -1.27820195e-01
    1.45348999e-01  -1.61779142e-01]
 [  3.53604328e-02   5.22105478e-02   1.30315656e-01 ...,  -2.42729619e-01
   -5.81702168e-02   1.34868180e-01]
 [  2.64244445e-04  -4.26927809e-03  -1.45666806e-01 ...,   1.62720685e-01
    7.17934897e-02   1.58529385e-01]
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 [ -1.94882976e-01  -1.77547201e-01  -1.10754700e-01 ...,   1.09894022e-01
   -5.13072149e-02  -1.58778772e-02]
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   -1.61389474e-03  -2.31837003e-01]
 [  6.35368550e-02  -3.78374080e-02  -8.05612297e-02 ...,   3.86244402e-02
    2.13464188e-01   2.02400339e-01]]
Progress: 3.7% ... Training loss: 0.308 ... Validation loss: 0.473[[ 0.29014433]
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[[  4.84865697e-02  -1.30013153e-01   3.51504853e-02 ...,  -1.27875606e-01
    1.45831291e-01  -1.62340167e-01]
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   -5.79362329e-02   1.34628849e-01]
 [  1.35267745e-03  -5.31167507e-03  -1.48831554e-01 ...,   1.62379188e-01
    7.47309587e-02   1.55775168e-01]
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 [ -1.94884865e-01  -1.77546971e-01  -1.10768795e-01 ...,   1.09893656e-01
   -5.13195306e-02  -1.58723137e-02]
 [ -2.77010555e-01  -2.21144432e-01  -4.73416378e-02 ...,  -1.15799547e-01
   -2.71029567e-04  -2.33140287e-01]
 [  6.37198305e-02  -3.80140818e-02  -8.11059373e-02 ...,   3.85660699e-02
    2.13970300e-01   2.01880914e-01]]
Progress: 3.7% ... Training loss: 0.304 ... Validation loss: 0.464[[ 0.28923057]
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[[ 0.04830006 -0.12982869  0.03581471 ..., -0.1278287   0.14520612
  -0.1617694 ]
 [ 0.03553272  0.05205791  0.12984808 ..., -0.24277686 -0.05771427
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 [-0.1945454  -0.17783405 -0.11163283 ...,  0.10979786 -0.05065332
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 [ 0.06334212 -0.03766156 -0.08000715 ...,  0.03867049  0.21303392
   0.20289971]]
Progress: 3.7% ... Training loss: 0.306 ... Validation loss: 0.463[[ 0.28708294]
 [-0.25835204]
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[[ 0.04804317 -0.12959339  0.03658945 ..., -0.12775271  0.14453419
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 [-0.19436361 -0.17799429 -0.11209382 ...,  0.10975203 -0.05021525
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 [ 0.06314971 -0.03748256 -0.07947821 ...,  0.03872694  0.21255579
   0.20344876]]
Progress: 3.7% ... Training loss: 0.308 ... Validation loss: 0.468[[ 0.29789484]
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[[ 0.04869349 -0.13017727  0.03490914 ..., -0.12793533  0.14600524
  -0.16268986]
 [ 0.03558158  0.05200116  0.12969523 ..., -0.24279179 -0.05750026
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 [-0.27667079 -0.22145763 -0.0482304  ..., -0.1158878   0.00055208
  -0.23387642]
 [ 0.06317705 -0.03750871 -0.07953884 ...,  0.03872138  0.21272485
   0.20338096]]
Progress: 3.7% ... Training loss: 0.314 ... Validation loss: 0.470[[ 0.28030588]
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[[  4.78465479e-02  -1.29407261e-01   3.73673793e-02 ...,  -1.27714191e-01
    1.43942523e-01  -1.60535357e-01]
 [  3.55406297e-02   5.20348018e-02   1.29805239e-01 ...,  -2.42781379e-01
   -5.76107163e-02   1.34329150e-01]
 [  1.22043516e-03  -5.31971647e-03  -1.48601752e-01 ...,   1.62373021e-01
    7.45730740e-02   1.56330993e-01]
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 [ -1.94203557e-01  -1.78134698e-01  -1.12450393e-01 ...,   1.09701048e-01
   -4.98876679e-02  -1.76779557e-02]
 [ -2.76796612e-01  -2.21349333e-01  -4.78819916e-02 ...,  -1.15858707e-01
    1.97348482e-04  -2.33565196e-01]
 [  6.28045114e-02  -3.71637888e-02  -7.84951940e-02 ...,   3.88122659e-02
    2.11785733e-01   2.04339079e-01]]
Progress: 3.7% ... Training loss: 0.319 ... Validation loss: 0.488[[ 0.29143966]
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[[ 0.04822082 -0.12977146  0.03626494 ..., -0.12785098  0.14527515
  -0.16129268]
 [ 0.03553587  0.05203914  0.12981817 ..., -0.24277987 -0.05762408
   0.13434196]
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 [-0.19415771 -0.17817746 -0.11256763 ...,  0.10969012 -0.04982685
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  -0.23447084]
 [ 0.06237711 -0.0367576  -0.07726984 ...,  0.03894204  0.21081969
   0.20554976]]
Progress: 3.7% ... Training loss: 0.304 ... Validation loss: 0.464[[ 0.28110314]
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[[ 0.04745427 -0.12908251  0.03859889 ..., -0.12764449  0.14305576
  -0.15915394]
 [ 0.03555214  0.05202499  0.12977375 ..., -0.24278345 -0.0575806
   0.13429963]
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   0.15881762]
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 [-0.19469144 -0.17771595 -0.11116525 ...,  0.10982334 -0.05124063
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  -0.2344781 ]
 [ 0.06179368 -0.03622619 -0.07563903 ...,  0.0390994   0.20938101
   0.20713016]]
Progress: 3.7% ... Training loss: 0.317 ... Validation loss: 0.486[[ 0.30288528]
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[[ 0.0493936  -0.13097165  0.03290285 ..., -0.12827599  0.14846183
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 [ 0.03592328  0.05166067  0.12865153 ..., -0.24290603 -0.0564986
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 [-0.19416539 -0.17821088 -0.11260995 ...,  0.10966075 -0.04989179
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  -0.2343558 ]
 [ 0.06252155 -0.03691721 -0.07774865 ...,  0.03886321  0.21140379
   0.20513277]]
Progress: 3.8% ... Training loss: 0.334 ... Validation loss: 0.486[[ 0.28007587]
 [-0.26471259]
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 [-0.83609142]
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 [ 1.06355145]
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 [ 0.03101609]
 [ 1.68984757]
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[[  4.84657080e-02  -1.30175876e-01   3.54555294e-02 ...,  -1.28041484e-01
    1.46026170e-01  -1.62172283e-01]
 [  3.58109492e-02   5.17526691e-02   1.28945395e-01 ...,  -2.42880401e-01
   -5.67597581e-02   1.33461553e-01]
 [  2.24555662e-03  -6.34841591e-03  -1.51417577e-01 ...,   1.62008217e-01
    7.76084591e-02   1.54106539e-01]
 ..., 
 [ -1.94909564e-01  -1.77606489e-01  -1.10707630e-01 ...,   1.09835791e-01
   -5.18644546e-02  -1.61132753e-02]
 [ -2.76950809e-01  -2.21252589e-01  -4.74823031e-02 ...,  -1.15850570e-01
   -1.43665886e-04  -2.33302169e-01]
 [  6.20276857e-02  -3.64793585e-02  -7.63573140e-02 ...,   3.89901210e-02
    2.10187707e-01   2.06433646e-01]]
Progress: 3.8% ... Training loss: 0.323 ... Validation loss: 0.487[[ 0.30414971]
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 [-0.81606666]
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 [ 1.09286506]
 [ 0.42887406]
 [-0.67150387]
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[[ 0.04925752 -0.13098297  0.03309397 ..., -0.12831289  0.14839963
  -0.16443623]
 [ 0.0357361   0.05182457  0.12916799 ..., -0.24285497 -0.05697415
   0.13367197]
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   0.20484262]]
Progress: 3.8% ... Training loss: 0.331 ... Validation loss: 0.483[[ 0.2878982 ]
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[[  4.80893222e-02  -1.30016281e-01   3.62299955e-02 ...,  -1.28037909e-01
    1.45311796e-01  -1.61579912e-01]
 [  3.57571231e-02   5.18106603e-02   1.29112562e-01 ...,  -2.42861192e-01
   -5.68946945e-02   1.33640441e-01]
 [  1.68887560e-03  -5.91828830e-03  -1.49883651e-01 ...,   1.62117000e-01
    7.63826919e-02   1.55528382e-01]
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 [ -1.94734470e-01  -1.77791865e-01  -1.11158574e-01 ...,   1.09772293e-01
   -5.14217356e-02  -1.65570553e-02]
 [ -2.76838375e-01  -2.21370954e-01  -4.78069769e-02 ...,  -1.15887393e-01
    1.43723327e-04  -2.33621856e-01]
 [  6.23836828e-02  -3.68549318e-02  -7.75285779e-02 ...,   3.88610516e-02
    2.11504421e-01   2.05282081e-01]]
Progress: 3.8% ... Training loss: 0.307 ... Validation loss: 0.467[[ 0.2951477 ]
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[[  4.84406103e-02  -1.30323127e-01   3.54048531e-02 ...,  -1.28139420e-01
    1.45966727e-01  -1.62343792e-01]
 [  3.60308743e-02   5.15601860e-02   1.28343742e-01 ...,  -2.42938663e-01
   -5.61667595e-02   1.32918180e-01]
 [  1.34098893e-03  -5.58989863e-03  -1.48723268e-01 ...,   1.62216952e-01
    7.53463781e-02   1.56682135e-01]
 ..., 
 [ -1.94855763e-01  -1.77684068e-01  -1.10809842e-01 ...,   1.09808925e-01
   -5.17822381e-02  -1.62568437e-02]
 [ -2.76868423e-01  -2.21347404e-01  -4.77227958e-02 ...,  -1.15881159e-01
    6.66893784e-05  -2.33509406e-01]
 [  6.24323093e-02  -3.68871442e-02  -7.76446686e-02 ...,   3.88487165e-02
    2.11590397e-01   2.05187812e-01]]
Progress: 3.8% ... Training loss: 0.307 ... Validation loss: 0.463[[ 0.29541026]
 [-0.25181696]
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[[ 0.04846027 -0.13031386  0.03539758 ..., -0.12814521  0.14602348
  -0.16224467]
 [ 0.03606644  0.05152947  0.12825096 ..., -0.24294732 -0.05608349
   0.13282792]
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   0.15882772]
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 [-0.19504687 -0.17751888 -0.11032934 ...,  0.10985958 -0.05231489
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  -0.23401705]
 [ 0.06241868 -0.0368676  -0.07759008 ...,  0.0388597   0.21169393
   0.2052683 ]]
Progress: 3.8% ... Training loss: 0.307 ... Validation loss: 0.467[[ 0.2914347 ]
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[[ 0.04810491 -0.12998976  0.03650667 ..., -0.12802598  0.14515075
  -0.16110017]
 [ 0.03598725  0.05159562  0.12846525 ..., -0.24292674 -0.05630027
   0.13302883]
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 [-0.19487985 -0.17767094 -0.11067407 ...,  0.10980945 -0.05182235
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  -0.23462521]
 [ 0.06163719 -0.03618828 -0.07553144 ...,  0.03907134  0.20991768
   0.20732379]]
Progress: 3.8% ... Training loss: 0.303 ... Validation loss: 0.467[[ 0.29501501]
 [-0.25352472]
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[[ 0.04824624 -0.13014144  0.03602272 ..., -0.1280724   0.1457445
  -0.16137785]
 [ 0.03598202  0.05159842  0.12847237 ..., -0.24292526 -0.05631094
   0.13304641]
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   0.16333101]
 ..., 
 [-0.19509346 -0.17748479 -0.11010756 ...,  0.10986843 -0.05241935
  -0.01565237]
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  -0.23355719]
 [ 0.06170218 -0.03623022 -0.07570151 ...,  0.03905507  0.21021315
   0.20722148]]
Progress: 3.8% ... Training loss: 0.305 ... Validation loss: 0.468[[ 0.29439057]
 [-0.25435437]
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[[ 0.04837597 -0.13022374  0.03588997 ..., -0.12809938  0.14583983
  -0.16152433]
 [ 0.0360347   0.05155303  0.12833062 ..., -0.24293919 -0.05616875
   0.13292421]
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   0.16408973]
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 [-0.19492984 -0.17762462 -0.11052392 ...,  0.1098209  -0.05205745
  -0.01604222]
 [-0.27655544 -0.22159963 -0.04846755 ..., -0.11596343  0.00081193
  -0.2340454 ]
 [ 0.06186207 -0.03637869 -0.07613206 ...,  0.03900853  0.21072319
   0.20681616]]
Progress: 3.8% ... Training loss: 0.304 ... Validation loss: 0.467[[ 0.29582108]
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[[ 0.04889154 -0.13070077  0.03454657 ..., -0.12824955  0.14727111
  -0.1626869 ]
 [ 0.03591423  0.05164693  0.1286669  ..., -0.24290597 -0.05652537
   0.13322687]
 [-0.00189111 -0.00274279 -0.13988136 ...,  0.16305808  0.0672449
   0.16584112]
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 [-0.19520185 -0.17739458 -0.10982917 ...,  0.10989336 -0.05281155
  -0.01534175]
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  -0.23455377]
 [ 0.06166101 -0.03620086 -0.07562426 ...,  0.03906288  0.21024309
   0.20738222]]
Progress: 3.8% ... Training loss: 0.305 ... Validation loss: 0.470[[ 0.28612728]
 [-0.26240702]
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[[ 0.04847574 -0.13035157  0.03572961 ..., -0.12813294  0.1461315
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 [ 0.03589812  0.05166076  0.12870429 ..., -0.2429012  -0.05657128
   0.13326888]
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   0.16628045]
 ..., 
 [-0.19546669 -0.17717025 -0.10913729 ...,  0.10996213 -0.05352675
  -0.01467997]
 [-0.27623553 -0.22187632 -0.04925549 ..., -0.11604486  0.00155443
  -0.23480273]
 [ 0.06131488 -0.03587663 -0.07466235 ...,  0.03916965  0.20941277
   0.20827444]]
Progress: 3.8% ... Training loss: 0.311 ... Validation loss: 0.475[[ 0.29460894]
 [-0.25481189]
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[[ 0.04892897 -0.13079772  0.03446198 ..., -0.12828067  0.14742105
  -0.16297056]
 [ 0.03606106  0.05151378  0.12824382 ..., -0.24295168 -0.05612041
   0.13287179]
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   0.1664286 ]
 ..., 
 [-0.19511059 -0.17749507 -0.11013203 ...,  0.10985302 -0.0525826
  -0.01563215]
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  -0.23454804]
 [ 0.06133367 -0.03588844 -0.07473142 ...,  0.03916648  0.2094575
   0.20827008]]
Progress: 3.8% ... Training loss: 0.303 ... Validation loss: 0.471[[ 0.29490847]
 [-0.25376294]
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[[ 0.0486397  -0.13053919  0.0353683  ..., -0.12819386  0.14653027
  -0.16215507]
 [ 0.03608833  0.05149049  0.12817558 ..., -0.24295927 -0.05604627
   0.13280745]
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   0.16629691]
 ..., 
 [-0.19520491 -0.17741052 -0.10985412 ...,  0.10987396 -0.05286681
  -0.01544478]
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  -0.23431187]
 [ 0.06140902 -0.03594103 -0.07491163 ...,  0.03915072  0.20972637
   0.20813405]]
Progress: 3.8% ... Training loss: 0.304 ... Validation loss: 0.470[[ 0.29800244]
 [-0.25207781]
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[[ 0.04884452 -0.13072172  0.03503716 ..., -0.12825326  0.14690063
  -0.16268469]
 [ 0.03621221  0.05138436  0.12786183 ..., -0.24299332 -0.05570799
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   0.16343997]
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 [-0.19521256 -0.17740877 -0.10983058 ...,  0.10987737 -0.05291821
  -0.015449  ]
 [-0.27645117 -0.22169273 -0.04863856 ..., -0.1159875   0.00089949
  -0.23428581]
 [ 0.06204618 -0.036507   -0.07668233 ...,  0.03897454  0.21158008
   0.20644463]]
Progress: 3.8% ... Training loss: 0.308 ... Validation loss: 0.468[[ 0.29487743]
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[[  4.93121408e-02  -1.31090169e-01   3.40717454e-02 ...,  -1.28371550e-01
    1.48019163e-01  -1.63630775e-01]
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 [ -1.77753486e-04  -4.35828181e-03  -1.44185676e-01 ...,   1.62531918e-01
    7.13774832e-02   1.61520974e-01]
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 [ -1.94982915e-01  -1.77599752e-01  -1.10403916e-01 ...,   1.09821439e-01
   -5.25172557e-02  -1.59919595e-02]
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    1.04394100e-03  -2.34358509e-01]
 [  6.25974294e-02  -3.69690850e-02  -7.80487050e-02 ...,   3.88358247e-02
    2.13024755e-01   2.05052950e-01]]
Progress: 3.8% ... Training loss: 0.305 ... Validation loss: 0.462[[ 0.28820476]
 [-0.26051221]
 [-0.80435726]
 [-0.83080013]
 [-0.23964637]
 [ 1.08490613]
 [ 0.41512165]
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[[ 0.04935827 -0.13110355  0.03416737 ..., -0.12835946  0.14795064
  -0.16375954]
 [ 0.03611775  0.05146603  0.12812113 ..., -0.24296939 -0.05593987
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 [-0.19522982 -0.17738848 -0.1097463  ...,  0.10988554 -0.05319251
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  -0.23388316]
 [ 0.06235972 -0.03674191 -0.07746693 ...,  0.03889145  0.21250492
   0.20563174]]
Progress: 3.9% ... Training loss: 0.305 ... Validation loss: 0.468[[ 0.29170444]
 [-0.25822114]
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[[  4.99245857e-02  -1.31559406e-01   3.28330267e-02 ...,  -1.28498167e-01
    1.49408223e-01  -1.64875786e-01]
 [  3.60279695e-02   5.15481681e-02   1.28348487e-01 ...,  -2.42942011e-01
   -5.61763223e-02   1.32941133e-01]
 [ -2.73189016e-04  -4.31880527e-03  -1.43715209e-01 ...,   1.62547980e-01
    7.11135010e-02   1.62227318e-01]
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 [ -1.95184533e-01  -1.77427409e-01  -1.09852568e-01 ...,   1.09869332e-01
   -5.31421462e-02  -1.55066612e-02]
 [ -2.76398753e-01  -2.21736223e-01  -4.87494219e-02 ...,  -1.16011978e-01
    1.08447384e-03  -2.34394581e-01]
 [  6.23750827e-02  -3.67426312e-02  -7.74979425e-02 ...,   3.88891526e-02
    2.12758921e-01   2.05634267e-01]]
Progress: 3.9% ... Training loss: 0.304 ... Validation loss: 0.461[[ 0.28633963]
 [-0.26211003]
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 [-0.83063901]
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 [ 1.08640727]
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[[ 0.04984968 -0.1314573   0.03325752 ..., -0.12845913  0.1489998
  -0.16455484]
 [ 0.03605288  0.0515198   0.12826884 ..., -0.24295066 -0.05609645
   0.13286265]
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 [-0.19486648 -0.17770538 -0.11066901 ...,  0.10978299 -0.05238264
  -0.01627897]
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  -0.23487707]
 [ 0.06199436 -0.03636398 -0.07636098 ...,  0.03899091  0.21189325
   0.20665278]]
Progress: 3.9% ... Training loss: 0.306 ... Validation loss: 0.467[[ 0.29658103]
 [-0.25497247]
 [-0.79560101]
 [-0.82209018]
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 [ 1.09336123]
 [ 0.42685717]
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[[ 0.05051676 -0.13206704  0.03142409 ..., -0.12865213  0.15070487
  -0.1661941 ]
 [ 0.0359379   0.05162508  0.12857858 ..., -0.24291671 -0.05637703
   0.13316774]
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 [-0.19439024 -0.17811186 -0.11193947 ...,  0.10963482 -0.05119038
  -0.0174684 ]
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  -0.23424717]
 [ 0.06187707 -0.03622674 -0.07598646 ...,  0.03902591  0.21173264
   0.2070115 ]]
Progress: 3.9% ... Training loss: 0.309 ... Validation loss: 0.470[[ 0.28723548]
 [-0.26457766]
 [-0.80295706]
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 [ 1.08696916]
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[[ 0.05002103 -0.13161274  0.03287823 ..., -0.12852034  0.14929671
  -0.1648801 ]
 [ 0.03585727  0.05168953  0.12877634 ..., -0.24289616 -0.05659788
   0.13336562]
 [-0.00124792 -0.00337039 -0.14065139 ...,  0.1628367   0.068299
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 [-0.19457368 -0.17795776 -0.11141526 ...,  0.10967747 -0.05170573
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  -0.23384544]
 [ 0.06183129 -0.03617913 -0.07585766 ...,  0.03904308  0.21172997
   0.20717462]]
Progress: 3.9% ... Training loss: 0.306 ... Validation loss: 0.466[[ 0.29270241]
 [-0.26078579]
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[[  5.00681293e-02  -1.31638341e-01   3.28033986e-02 ...,  -1.28536605e-01
    1.49408485e-01  -1.64699706e-01]
 [  3.59412187e-02   5.16146876e-02   1.28542694e-01 ...,  -2.42920276e-01
   -5.63751980e-02   1.33148692e-01]
 [ -1.20046370e-03  -3.39626872e-03  -1.40739789e-01 ...,   1.62825164e-01
    6.83425314e-02   1.65436577e-01]
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 [ -1.94494112e-01  -1.78032799e-01  -1.11623761e-01 ...,   1.09654488e-01
   -5.15166353e-02  -1.73032476e-02]
 [ -2.76734120e-01  -2.21422062e-01  -4.78005114e-02 ...,  -1.15919860e-01
    2.59328495e-05  -2.33522310e-01]
 [  6.16961431e-02  -3.60549839e-02  -7.54262373e-02 ...,   3.90880712e-02
    2.11505166e-01   2.07594517e-01]]
Progress: 3.9% ... Training loss: 0.304 ... Validation loss: 0.463[[ 0.28907153]
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[[  5.00732332e-02  -1.31639558e-01   3.29627049e-02 ...,  -1.28539097e-01
    1.49186980e-01  -1.64675615e-01]
 [  3.59020917e-02   5.16509492e-02   1.28650375e-01 ...,  -2.42909759e-01
   -5.64877186e-02   1.33254035e-01]
 [ -2.12523260e-03  -2.67846158e-03  -1.38460020e-01 ...,   1.63033207e-01
    6.59608965e-02   1.67813797e-01]
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 [ -1.94601946e-01  -1.77938275e-01  -1.11236554e-01 ...,   1.09677717e-01
   -5.18387224e-02  -1.70346694e-02]
 [ -2.76836167e-01  -2.21328259e-01  -4.75242400e-02 ...,  -1.15891424e-01
   -2.51695581e-04  -2.33233281e-01]
 [  6.21675342e-02  -3.64715511e-02  -7.66848103e-02 ...,   3.89586565e-02
    2.12786598e-01   2.06395352e-01]]
Progress: 3.9% ... Training loss: 0.304 ... Validation loss: 0.466[[ 0.2982662 ]
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[[ 0.05063304 -0.13218697  0.03143529 ..., -0.1286949   0.15076107
  -0.16622996]
 [ 0.03612225  0.05145085  0.12803614 ..., -0.24297035 -0.05588371
   0.13266837]
 [-0.00371601 -0.0012143  -0.13415469 ...,  0.16344923  0.06175735
   0.17215933]
 ..., 
 [-0.19452561 -0.17800585 -0.11149791 ...,  0.10965613 -0.05162985
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  -0.23300833]
 [ 0.0626565  -0.03691845 -0.07798527 ...,  0.03882375  0.2141338
   0.20507022]]
Progress: 3.9% ... Training loss: 0.311 ... Validation loss: 0.479[[ 0.29142304]
 [-0.26176375]
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[[ 0.05034888 -0.13194995  0.03229887 ..., -0.12863293  0.14974716
  -0.16544401]
 [ 0.03606746  0.05149703  0.12818227 ..., -0.24295632 -0.05603368
   0.1327726 ]
 [-0.00354264 -0.00138734 -0.13462274 ...,  0.16337836  0.06212587
   0.17189201]
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 [-0.19471455 -0.17785269 -0.11100226 ...,  0.10970132 -0.05227392
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  -0.23206882]
 [ 0.0627819  -0.03702278 -0.07830168 ...,  0.03879357  0.21440165
   0.20477898]]
Progress: 3.9% ... Training loss: 0.303 ... Validation loss: 0.470[[ 0.29605744]
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[[ 0.05016086 -0.13175782  0.03291619 ..., -0.12857768  0.14900569
  -0.16507911]
 [ 0.03610479  0.0514667   0.12808563 ..., -0.24296696 -0.0559489
   0.13268579]
 [-0.00232529 -0.0025499  -0.13787932 ...,  0.16302218  0.06519824
   0.16890773]
 ..., 
 [-0.19442467 -0.17809678 -0.11179001 ...,  0.10962082 -0.05152757
  -0.01751863]
 [-0.27761593 -0.22065676 -0.04544715 ..., -0.11569166 -0.00231625
  -0.23125078]
 [ 0.06328755 -0.03748889 -0.07968896 ...,  0.0386507   0.21576153
   0.20347025]]
Progress: 3.9% ... Training loss: 0.303 ... Validation loss: 0.469[[ 0.29159893]
 [-0.26256857]
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[[ 0.04991648 -0.13155771  0.03367556 ..., -0.12851567  0.1483295
  -0.16448409]
 [ 0.0361354   0.05143977  0.12800226 ..., -0.24297494 -0.05586599
   0.13260823]
 [-0.00065559 -0.00413024 -0.14247387 ...,  0.16254677  0.06968628
   0.16470397]
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 [-0.19455406 -0.17798829 -0.11142361 ...,  0.10965539 -0.0519234
  -0.0172022 ]
 [-0.27796509 -0.22035926 -0.0445417  ..., -0.11560573 -0.00320382
  -0.23046118]
 [ 0.06318957 -0.03738368 -0.07939806 ...,  0.03867861  0.21554397
   0.20361058]]
Progress: 3.9% ... Training loss: 0.303 ... Validation loss: 0.468[[ 0.29767911]
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[[  5.02468179e-02  -1.31845555e-01   3.28405204e-02 ...,  -1.28620717e-01
    1.49211870e-01  -1.65337444e-01]
 [  3.61551331e-02   5.14221188e-02   1.27953206e-01 ...,  -2.42980219e-01
   -5.58125943e-02   1.32555390e-01]
 [ -2.16276123e-04  -4.57107544e-03  -1.43721273e-01 ...,   1.62403742e-01
    7.07602471e-02   1.63630559e-01]
 ..., 
 [ -1.94363197e-01  -1.78159320e-01  -1.11962169e-01 ...,   1.09602770e-01
   -5.13945294e-02  -1.76203974e-02]
 [ -2.77756433e-01  -2.20547564e-01  -4.50886989e-02 ...,  -1.15668748e-01
   -2.60137996e-03  -2.30970520e-01]
 [  6.33310467e-02  -3.75032141e-02  -7.97062037e-02 ...,   3.86385424e-02
    2.15964270e-01   2.03252304e-01]]
Progress: 3.9% ... Training loss: 0.306 ... Validation loss: 0.468[[ 0.28416984]
 [-0.27071816]
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[[  4.96644000e-02  -1.31303831e-01   3.44507668e-02 ...,  -1.28462657e-01
    1.47707084e-01  -1.63675357e-01]
 [  3.61128041e-02   5.14532870e-02   1.28052627e-01 ...,  -2.42970770e-01
   -5.59063005e-02   1.32680346e-01]
 [ -1.40900135e-05  -4.74319602e-03  -1.44245569e-01 ...,   1.62341659e-01
    7.13861886e-02   1.63236196e-01]
 ..., 
 [ -1.94411853e-01  -1.78110875e-01  -1.11830933e-01 ...,   1.09618524e-01
   -5.15136820e-02  -1.75306543e-02]
 [ -2.77882732e-01  -2.20438199e-01  -4.47510602e-02 ...,  -1.15639266e-01
   -2.99924587e-03  -2.30702691e-01]
 [  6.26880179e-02  -3.69441586e-02  -7.80280533e-02 ...,   3.88123000e-02
    2.14340250e-01   2.04855646e-01]]
Progress: 3.9% ... Training loss: 0.317 ... Validation loss: 0.481[[ 0.29309769]
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[[ 0.05001007 -0.13164447  0.03357692 ..., -0.1285849   0.14888546
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   0.20489933]]
Progress: 3.9% ... Training loss: 0.302 ... Validation loss: 0.464[[ 0.2934648 ]
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[[ 0.05012222 -0.13171701  0.03341193 ..., -0.12860944  0.14920511
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   0.20539732]]
Progress: 3.9% ... Training loss: 0.302 ... Validation loss: 0.464[[ 0.29657122]
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[[  5.06109027e-02  -1.32173657e-01   3.20314311e-02 ...,  -1.28750279e-01
    1.50494612e-01  -1.65782029e-01]
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   -5.60245943e-02   1.33002100e-01]
 [ -2.12862703e-04  -4.62056828e-03  -1.43898336e-01 ...,   1.62364947e-01
    7.10359035e-02   1.63707083e-01]
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   -1.75099222e-03  -2.31816463e-01]
 [  6.22949381e-02  -3.65745998e-02  -7.69170996e-02 ...,   3.89184201e-02
    2.13642627e-01   2.05929289e-01]]
Progress: 4.0% ... Training loss: 0.305 ... Validation loss: 0.461[[ 0.28668371]
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[[ 0.05028961 -0.13184003  0.03303647 ..., -0.12866772  0.14941921
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   0.20741906]]
Progress: 4.0% ... Training loss: 0.309 ... Validation loss: 0.466[[ 0.30377072]
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[[  5.11956482e-02  -1.32692817e-01   3.08206487e-02 ...,  -1.28915516e-01
    1.51817878e-01  -1.66855404e-01]
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 [ -1.64307301e-04  -4.69192093e-03  -1.43621209e-01 ...,   1.62339442e-01
    7.10859163e-02   1.64003060e-01]
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 [ -1.93579408e-01  -1.78890154e-01  -1.14019155e-01 ...,   1.09378736e-01
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 [ -2.76878443e-01  -2.21326927e-01  -4.72985944e-02 ...,  -1.15907906e-01
   -5.68524534e-04  -2.33071879e-01]
 [  6.20712608e-02  -3.63890890e-02  -7.64465187e-02 ...,   3.89651884e-02
    2.13323412e-01   2.06503514e-01]]
Progress: 4.0% ... Training loss: 0.330 ... Validation loss: 0.483[[ 0.27768697]
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[[ 0.04925642 -0.13101927  0.03594593 ..., -0.12847976  0.1467522
  -0.16195546]
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   0.20646326]]
Progress: 4.0% ... Training loss: 0.346 ... Validation loss: 0.500[[ 0.29363746]
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[[ 0.05016876 -0.1319598   0.03345049 ..., -0.12876532  0.14925783
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   0.20586341]]
Progress: 4.0% ... Training loss: 0.304 ... Validation loss: 0.461[[ 0.2862828 ]
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[[ 0.04933117 -0.13115297  0.03583421 ..., -0.12854056  0.14709965
  -0.16215987]
 [ 0.0359641   0.05158141  0.12837451 ..., -0.24293393 -0.0560701
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   0.2066603 ]]
Progress: 4.0% ... Training loss: 0.307 ... Validation loss: 0.464[[ 0.29877524]
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[[ 0.04968848 -0.13154923  0.03469018 ..., -0.1286578   0.14819197
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 [-0.19379642 -0.17875352 -0.11351681 ...,  0.10940698 -0.05009389
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   0.20604797]]
Progress: 4.0% ... Training loss: 0.309 ... Validation loss: 0.472[[ 0.2884531 ]
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[[ 0.04870013 -0.13066131  0.03741193 ..., -0.12841016  0.14568141
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 [-0.19373656 -0.17879829 -0.11366655 ...,  0.10939224 -0.05001025
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   0.20645221]]
Progress: 4.0% ... Training loss: 0.308 ... Validation loss: 0.466[[ 0.3029956 ]
 [-0.25845566]
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[[ 0.05020513 -0.13210032  0.03326669 ..., -0.1288243   0.14979051
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 [-0.19358309 -0.17894811 -0.11403189 ...,  0.10934926 -0.0495696
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 [ 0.06196678 -0.0362888  -0.07625743 ...,  0.03900161  0.21389237
   0.20680436]]
Progress: 4.0% ... Training loss: 0.320 ... Validation loss: 0.483[[ 0.28934564]
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[[ 0.04987709 -0.13177821  0.03431088 ..., -0.12873405  0.14881827
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   0.20762295]]
Progress: 4.0% ... Training loss: 0.305 ... Validation loss: 0.463[[ 0.29024229]
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[[  4.91396987e-02  -1.31053681e-01   3.64323553e-02 ...,  -1.28512945e-01
    1.46654494e-01  -1.61589665e-01]
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 [ -3.25986724e-03  -2.52856260e-03  -1.36285575e-01 ...,   1.62877697e-01
    6.33174953e-02   1.71880487e-01]
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 [ -1.93763257e-01  -1.78799101e-01  -1.13533089e-01 ...,   1.09385134e-01
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    1.76564721e-04  -2.34482618e-01]
 [  6.15124842e-02  -3.58340012e-02  -7.49879904e-02 ...,   3.91232252e-02
    2.13043757e-01   2.08040608e-01]]
Progress: 4.0% ... Training loss: 0.303 ... Validation loss: 0.464[[ 0.284194  ]
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[[ 0.04877191 -0.13068968  0.03765723 ..., -0.12841293  0.14563118
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   0.20774294]]
Progress: 4.0% ... Training loss: 0.317 ... Validation loss: 0.475[[ 0.3033256 ]
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[[ 0.05048889 -0.13235597  0.03289483 ..., -0.12892684  0.15009221
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 [ 0.06196334 -0.03625052 -0.07620938 ...,  0.03900136  0.21446976
   0.20688811]]
Progress: 4.0% ... Training loss: 0.321 ... Validation loss: 0.483[[ 0.28649495]
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[[ 0.0494357  -0.13142202  0.03573219 ..., -0.12868861  0.14733372
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   0.20827334]]
Progress: 4.0% ... Training loss: 0.311 ... Validation loss: 0.466[[ 0.28606358]
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[[ 0.04929822 -0.13130179  0.03622348 ..., -0.12865049  0.14707382
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   0.20877974]]
Progress: 4.0% ... Training loss: 0.312 ... Validation loss: 0.471[[ 0.29594518]
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[[ 0.04932049 -0.13131099  0.03627342 ..., -0.12865549  0.14694368
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   0.20759623]]
Progress: 4.1% ... Training loss: 0.303 ... Validation loss: 0.470[[ 0.29082129]
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[[ 0.04906923 -0.13105298  0.03709678 ..., -0.1285811   0.14637448
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   0.2076808 ]]
Progress: 4.1% ... Training loss: 0.304 ... Validation loss: 0.467[[ 0.28613148]
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[[  4.87436755e-02  -1.30746636e-01   3.79856727e-02 ...,  -1.28490211e-01
    1.45636032e-01  -1.60183014e-01]
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   -5.38824871e-02   1.31072408e-01]
 [ -5.20438573e-03  -9.16076067e-04  -1.30617723e-01 ...,   1.63282792e-01
    5.84044016e-02   1.77554634e-01]
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 [ -1.94206634e-01  -1.78410357e-01  -1.12370888e-01 ...,   1.09476075e-01
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   -1.38311119e-05  -2.34409898e-01]
 [  6.17673665e-02  -3.60872943e-02  -7.54780993e-02 ...,   3.90427523e-02
    2.14500643e-01   2.07428961e-01]]
Progress: 4.1% ... Training loss: 0.311 ... Validation loss: 0.470[[ 0.29785733]
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[[ 0.04901789 -0.13103906  0.03712066 ..., -0.12857237  0.1462201
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   0.20636924]]
Progress: 4.1% ... Training loss: 0.306 ... Validation loss: 0.471[[ 0.28617206]
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[[ 0.0481356  -0.13023161  0.03956179 ..., -0.12834066  0.14368819
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 [-0.19414865 -0.17847117 -0.11252824 ...,  0.109468   -0.05138154
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  -0.234793  ]
 [ 0.06228101 -0.03657428 -0.07691357 ...,  0.03889817  0.21581192
   0.206042  ]]
Progress: 4.1% ... Training loss: 0.310 ... Validation loss: 0.473[[ 0.29238727]
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[[ 0.0486422  -0.13071834  0.03815784 ..., -0.12848934  0.14493212
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 [-0.19417094 -0.17846302 -0.11246399 ...,  0.10947279 -0.05147781
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   0.20683664]]
Progress: 4.1% ... Training loss: 0.301 ... Validation loss: 0.467[[ 0.30165065]
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[[ 0.04959825 -0.13156355  0.0356943  ..., -0.12873816  0.14721786
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 [-0.19364345 -0.17894144 -0.11382781 ...,  0.10933324 -0.05026251
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   0.20667212]]
Progress: 4.1% ... Training loss: 0.317 ... Validation loss: 0.481[[ 0.29136587]
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[[ 0.04909415 -0.13112156  0.0370812  ..., -0.12862777  0.14575004
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 [-0.19420222 -0.17846889 -0.112436   ...,  0.10946522 -0.05176181
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 [ 0.06219316 -0.03647907 -0.0766847  ...,  0.03891548  0.21578554
   0.20624506]]
Progress: 4.1% ... Training loss: 0.301 ... Validation loss: 0.464[[ 0.28650615]
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[[ 0.04887044 -0.13090929  0.03784429 ..., -0.1285705   0.14513219
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   0.20526687]]
Progress: 4.1% ... Training loss: 0.307 ... Validation loss: 0.472[[ 0.28935675]
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[[ 0.04907894 -0.13110797  0.03733461 ..., -0.12863466  0.14560486
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   0.20508458]]
Progress: 4.1% ... Training loss: 0.303 ... Validation loss: 0.471[[ 0.29748475]
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[[ 0.05003803 -0.13202121  0.03489128 ..., -0.12891631  0.14815871
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   0.20494086]]
Progress: 4.1% ... Training loss: 0.305 ... Validation loss: 0.475[[ 0.29043333]
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[[ 0.04929287 -0.13138547  0.03695069 ..., -0.12873268  0.146255
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Progress: 4.1% ... Training loss: 0.303 ... Validation loss: 0.469[[ 0.29703702]
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   0.20411193]]
Progress: 4.1% ... Training loss: 0.304 ... Validation loss: 0.471[[ 0.27969314]
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[[ 0.04879485 -0.13086983  0.03873879 ..., -0.12860675  0.14473668
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   0.20592285]]
Progress: 4.1% ... Training loss: 0.329 ... Validation loss: 0.489[[ 0.29427117]
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[[ 0.0498003  -0.13187612  0.03606313 ..., -0.12891461  0.14748972
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   0.20598421]]
Progress: 4.1% ... Training loss: 0.303 ... Validation loss: 0.466[[ 0.2824372 ]
 [-0.27442856]
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   0.20648726]]
Progress: 4.2% ... Training loss: 0.320 ... Validation loss: 0.484[[ 0.30290226]
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[[ 0.04994476 -0.13214183  0.0357851  ..., -0.12902029  0.14780897
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   0.20555673]]
Progress: 4.2% ... Training loss: 0.320 ... Validation loss: 0.473[[ 0.27977241]
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   0.20685272]]
Progress: 4.2% ... Training loss: 0.335 ... Validation loss: 0.499[[ 0.30462807]
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   0.20551557]]
Progress: 4.2% ... Training loss: 0.325 ... Validation loss: 0.484[[ 0.28467789]
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[[ 0.04851913 -0.13115583  0.03929734 ..., -0.12885294  0.14408329
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   0.20694618]]
Progress: 4.2% ... Training loss: 0.316 ... Validation loss: 0.480[[ 0.29005268]
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   0.20608799]]
Progress: 4.2% ... Training loss: 0.303 ... Validation loss: 0.467[[ 0.30044171]
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[[ 0.04907306 -0.13167615  0.03787455 ..., -0.1290166   0.14530173
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   0.20531088]]
Progress: 4.2% ... Training loss: 0.310 ... Validation loss: 0.473[[ 0.28543444]
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[[ 0.04757342 -0.13038228  0.04189845 ..., -0.12866014  0.14144368
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   0.2067343 ]]
Progress: 4.2% ... Training loss: 0.316 ... Validation loss: 0.482[[ 0.29900073]
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[[ 0.04856639 -0.13133305  0.03926644 ..., -0.1289481   0.14382032
  -0.160832  ]
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 [ 0.06225419 -0.03665226 -0.0769597  ...,  0.03877769  0.21734972
   0.20563722]]
Progress: 4.2% ... Training loss: 0.306 ... Validation loss: 0.474[[ 0.28862304]
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[[ 0.04746286 -0.13036439  0.04228696 ..., -0.12866944  0.14084739
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   0.20606195]]
Progress: 4.2% ... Training loss: 0.309 ... Validation loss: 0.475[[ 0.29883307]
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[[ 0.04794721 -0.13082861  0.04099969 ..., -0.12881808  0.14228894
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 [ 0.03684174  0.05064072  0.12562162 ..., -0.24322357 -0.05343407
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 [ 0.06245143 -0.03684723 -0.0774951  ...,  0.03871087  0.21819651
   0.205131  ]]
Progress: 4.2% ... Training loss: 0.302 ... Validation loss: 0.464[[ 0.30285745]
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   0.20501547]]
Progress: 4.2% ... Training loss: 0.309 ... Validation loss: 0.473[[ 0.28565017]
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[[ 0.04756942 -0.13053799  0.04199876 ..., -0.12875463  0.14109442
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   0.20594558]]
Progress: 4.2% ... Training loss: 0.324 ... Validation loss: 0.488[[ 0.30063976]
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[[ 0.04898858 -0.13193139  0.03804316 ..., -0.12917977  0.14490882
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   0.20451696]]
Progress: 4.2% ... Training loss: 0.305 ... Validation loss: 0.471[[ 0.29831635]
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   0.20547016]]
Progress: 4.2% ... Training loss: 0.301 ... Validation loss: 0.465[[ 0.28876865]
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[[ 0.04812237 -0.13117739  0.04048776 ..., -0.12893822  0.14252347
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   0.20678975]]
Progress: 4.3% ... Training loss: 0.312 ... Validation loss: 0.477[[ 0.30019254]
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[[ 0.04867886 -0.13171971  0.03903224 ..., -0.12910534  0.14400199
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   0.20628516]]
Progress: 4.3% ... Training loss: 0.303 ... Validation loss: 0.469[[ 0.30014562]
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[[ 0.04851106 -0.13156873  0.03949708 ..., -0.12907443  0.14356098
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   0.207221  ]]
Progress: 4.3% ... Training loss: 0.302 ... Validation loss: 0.466[[ 0.29485458]
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[[ 0.04859317 -0.13162984  0.03943046 ..., -0.12908627  0.14334141
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   0.20697124]]
Progress: 4.3% ... Training loss: 0.303 ... Validation loss: 0.468[[ 0.30166938]
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[[ 0.04897147 -0.1319695   0.03853323 ..., -0.12919914  0.14435848
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   0.20735554]]
Progress: 4.3% ... Training loss: 0.303 ... Validation loss: 0.467[[ 0.30288373]
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[[ 0.04902506 -0.13202111  0.03838463 ..., -0.1292164   0.14451159
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   0.20679587]]
Progress: 4.3% ... Training loss: 0.304 ... Validation loss: 0.464[[ 0.29625752]
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[[ 0.04834779 -0.1314204   0.04018212 ..., -0.12904859  0.14273256
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   0.20741439]]
Progress: 4.3% ... Training loss: 0.302 ... Validation loss: 0.468[[ 0.30350437]
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[[ 0.04846366 -0.13153271  0.040005   ..., -0.12906554  0.14295205
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   0.20623159]]
Progress: 4.3% ... Training loss: 0.304 ... Validation loss: 0.472[[ 0.30385806]
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[[ 0.04894042 -0.13194205  0.03892581 ..., -0.12919245  0.14403607
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   0.20464917]]
Progress: 4.3% ... Training loss: 0.304 ... Validation loss: 0.469[[ 0.29732027]
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[[ 0.04852759 -0.13157058  0.04010349 ..., -0.12908036  0.14299776
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   0.20406507]]
Progress: 4.3% ... Training loss: 0.301 ... Validation loss: 0.467[[ 0.29030781]
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   0.20465571]]
Progress: 4.3% ... Training loss: 0.314 ... Validation loss: 0.482[[ 0.30230855]
 [-0.26738661]
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[[ 0.0491896  -0.13215395  0.03855976 ..., -0.12927385  0.14468448
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 [ 0.03674457  0.0507312   0.12589315 ..., -0.24319018 -0.05367738
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   0.20392571]]
Progress: 4.3% ... Training loss: 0.303 ... Validation loss: 0.462[[ 0.29936009]
 [-0.27096756]
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[[ 0.04924748 -0.1322403   0.03836848 ..., -0.12928471  0.14476555
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   0.20380505]]
Progress: 4.3% ... Training loss: 0.301 ... Validation loss: 0.464[[ 0.30156086]
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[[ 0.04936214 -0.13233422  0.03810324 ..., -0.12930276  0.14487238
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   0.20340886]]
Progress: 4.3% ... Training loss: 0.302 ... Validation loss: 0.465[[ 0.29873401]
 [-0.27182085]
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 [ 1.10039557]
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[[ 0.04923233 -0.13219767  0.03850536 ..., -0.12928023  0.14451731
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 [ 0.03682816  0.05066089  0.1257005  ..., -0.24320906 -0.05345158
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  -0.23268957]
 [ 0.06269283 -0.03702687 -0.07808941 ...,  0.03866183  0.21989193
   0.20414084]]
Progress: 4.3% ... Training loss: 0.301 ... Validation loss: 0.463[[ 0.30206972]
 [-0.26979689]
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 [-0.83536611]
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 [ 1.10480478]
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[[ 0.04945574 -0.13242925  0.03787317 ..., -0.12934825  0.14517336
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   0.20421492]]
Progress: 4.4% ... Training loss: 0.302 ... Validation loss: 0.466[[ 0.29349407]
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[[ 0.04878415 -0.13182668  0.03970407 ..., -0.12916251  0.14354893
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 [-0.19435063 -0.17863464 -0.11200622 ...,  0.10929584 -0.05330331
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 [ 0.06301485 -0.03729951 -0.07884965 ...,  0.03858779  0.22082428
   0.2033757 ]]
Progress: 4.4% ... Training loss: 0.306 ... Validation loss: 0.474[[ 0.29805722]
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[[ 0.04917179 -0.13218702  0.03880742 ..., -0.12927123  0.14436846
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 [ 0.0632886  -0.03753846 -0.07961294 ...,  0.03851909  0.22159428
   0.20266419]]
Progress: 4.4% ... Training loss: 0.300 ... Validation loss: 0.466[[ 0.29358248]
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[[ 0.0487286  -0.13176493  0.04008906 ..., -0.12915094  0.14326827
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 [ 0.03659548  0.05086797  0.12631675 ..., -0.24314956 -0.05404847
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 [ 0.06252715 -0.03681731 -0.07755821 ...,  0.03872431  0.21980392
   0.20465587]]
Progress: 4.4% ... Training loss: 0.306 ... Validation loss: 0.473[[ 0.29970733]
 [-0.26930877]
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[[  4.93123342e-02  -1.32263555e-01   3.87009769e-02 ...,  -1.29300049e-01
    1.44955917e-01  -1.62804221e-01]
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   -5.36564215e-02   1.30492478e-01]
 [ -7.53536809e-03  -2.65120021e-04  -1.24942264e-01 ...,   1.63170616e-01
    5.33986835e-02   1.87766628e-01]
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 [ -1.94079948e-01  -1.78882844e-01  -1.12656830e-01 ...,   1.09224007e-01
   -5.27747185e-02  -1.91232719e-02]
 [ -2.78206468e-01  -2.20663848e-01  -4.42911496e-02 ...,  -1.15875132e-01
   -4.71270336e-03  -2.31600481e-01]
 [  6.26401722e-02  -3.69169899e-02  -7.78443386e-02 ...,   3.87003911e-02
    2.20239803e-01   2.04393009e-01]]
Progress: 4.4% ... Training loss: 0.300 ... Validation loss: 0.464[[ 0.29765972]
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[[ 0.04926271 -0.13222948  0.03877899 ..., -0.12928194  0.14504835
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 [-0.1941434  -0.17883059 -0.11250675 ...,  0.10923635 -0.05301511
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  -0.2319444 ]
 [ 0.06246225 -0.03674063 -0.07734678 ...,  0.03875448  0.21991053
   0.20492911]]
Progress: 4.4% ... Training loss: 0.301 ... Validation loss: 0.469[[ 0.29466991]
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[[  5.00343042e-02  -1.32921974e-01   3.68848287e-02 ...,  -1.29489392e-01
    1.47177791e-01  -1.64546035e-01]
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   -5.37114442e-02   1.30591076e-01]
 [ -7.76615160e-03  -6.50791660e-05  -1.24252110e-01 ...,   1.63208254e-01
    5.32709340e-02   1.88892768e-01]
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 [ -1.93995982e-01  -1.78964016e-01  -1.12907484e-01 ...,   1.09203714e-01
   -5.26203951e-02  -1.94063873e-02]
 [ -2.78292310e-01  -2.20579925e-01  -4.40624315e-02 ...,  -1.15847315e-01
   -4.95995801e-03  -2.31383333e-01]
 [  6.25430147e-02  -3.68096319e-02  -7.75072163e-02 ...,   3.87335588e-02
    2.20187985e-01   2.04758265e-01]]
Progress: 4.4% ... Training loss: 0.302 ... Validation loss: 0.469[[ 0.30005753]
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[[ 0.04994324 -0.13281703  0.03721442 ..., -0.1294547   0.14695074
  -0.1641054 ]
 [ 0.03677953  0.050706    0.12578548 ..., -0.24319696 -0.0535289
   0.13039626]
 [-0.00838956  0.00056237 -0.12247303 ...,  0.16338991  0.051536
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 [-0.194018   -0.17894376 -0.11285423 ...,  0.10921078 -0.05263862
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  -0.23160595]
 [ 0.06293204 -0.03717044 -0.0785581  ...,  0.03862796  0.22133646
   0.20370958]]
Progress: 4.4% ... Training loss: 0.301 ... Validation loss: 0.468[[ 0.30121919]
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[[ 0.04993569 -0.13279966  0.03733562 ..., -0.12946116  0.14712386
  -0.16384949]
 [ 0.03660191  0.05086068  0.12624561 ..., -0.24315481 -0.05399515
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 [-0.19427808 -0.1787089  -0.11213292 ...,  0.10927567 -0.05334479
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 [ 0.06311379 -0.03733157 -0.07901463 ...,  0.03858163  0.22199308
   0.20318849]]
Progress: 4.4% ... Training loss: 0.301 ... Validation loss: 0.464[[ 0.29473931]
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[[  4.98445410e-02  -1.32667906e-01   3.77713234e-02 ...,  -1.29429315e-01
    1.46730336e-01  -1.63647336e-01]
 [  3.64793736e-02   5.09780712e-02   1.26608023e-01 ...,  -2.43122756e-01
   -5.43164613e-02   1.31086401e-01]
 [ -7.59969070e-03  -2.21947751e-04  -1.24549762e-01 ...,   1.63169244e-01
    5.35167476e-02   1.89132360e-01]
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 [ -1.93912288e-01  -1.79016347e-01  -1.13074528e-01 ...,   1.09189505e-01
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   -4.11931095e-03  -2.32192443e-01]
 [  6.32394854e-02  -3.74489288e-02  -7.93453205e-02 ...,   3.85493224e-02
    2.22329291e-01   2.02881038e-01]]
Progress: 4.4% ... Training loss: 0.302 ... Validation loss: 0.467[[ 0.30049563]
 [-0.27118469]
 [-0.79981158]
 [-0.83466207]
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 [ 1.10488646]
 [ 0.42036553]
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 [ 0.72470218]
 [ 0.12870291]
 [ 0.27618002]
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 [ 0.39592368]
 [ 1.08346756]
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 [ 1.72755079]
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[[ 0.05014738 -0.13294623  0.03698845 ..., -0.12949648  0.14723949
  -0.16449003]
 [ 0.03660316  0.05086485  0.12628428 ..., -0.2431535  -0.05398512
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 [-0.19377139 -0.17914234 -0.11342911 ...,  0.10915163 -0.05222238
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  -0.23286534]
 [ 0.06350708 -0.03770218 -0.08011681 ...,  0.0384801   0.22309281
   0.20222695]]
Progress: 4.4% ... Training loss: 0.301 ... Validation loss: 0.467[[ 0.2918465 ]
 [-0.27944551]
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 [ 0.41275584]
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[[  4.94494521e-02  -1.32308371e-01   3.88682536e-02 ...,  -1.29325189e-01
    1.45466614e-01  -1.62707175e-01]
 [  3.65101696e-02   5.09482374e-02   1.26528397e-01 ...,  -2.43130728e-01
   -5.42180000e-02   1.31031440e-01]
 [ -7.75428191e-03  -1.25183296e-04  -1.24195127e-01 ...,   1.63173078e-01
    5.32208139e-02   1.89595957e-01]
 ..., 
 [ -1.93698348e-01  -1.79202871e-01  -1.13593929e-01 ...,   1.09135801e-01
   -5.20977867e-02  -2.00515644e-02]
 [ -2.77661255e-01  -2.21142863e-01  -4.57348088e-02 ...,  -1.15988645e-01
   -3.48144624e-03  -2.32992550e-01]
 [  6.33612562e-02  -3.75452953e-02  -7.96604555e-02 ...,   3.85216051e-02
    2.22783258e-01   2.02698481e-01]]
Progress: 4.4% ... Training loss: 0.308 ... Validation loss: 0.476[[ 0.29673786]
 [-0.27555156]
 [-0.80319611]
 [-0.83714758]
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 [ 1.10316763]
 [ 0.41573538]
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[[  4.97776384e-02  -1.32628108e-01   3.79864710e-02 ...,  -1.29408807e-01
    1.46594154e-01  -1.63538385e-01]
 [  3.65893246e-02   5.08708184e-02   1.26304772e-01 ...,  -2.43150917e-01
   -5.40012500e-02   1.30815924e-01]
 [ -7.75056871e-03  -1.38175625e-04  -1.24225484e-01 ...,   1.63161536e-01
    5.30654434e-02   1.89724103e-01]
 ..., 
 [ -1.93849732e-01  -1.79057547e-01  -1.13201313e-01 ...,   1.09176541e-01
   -5.25473043e-02  -1.96490194e-02]
 [ -2.77313061e-01  -2.21468021e-01  -4.66696924e-02 ...,  -1.16083390e-01
   -2.58616991e-03  -2.33836990e-01]
 [  6.27053161e-02  -3.68841794e-02  -7.77562258e-02 ...,   3.87081361e-02
    2.21277254e-01   2.04424878e-01]]
Progress: 4.4% ... Training loss: 0.301 ... Validation loss: 0.469[[ 0.2971331 ]
 [-0.27600823]
 [-0.80427561]
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[[ 0.04975432 -0.13261624  0.03817669 ..., -0.12941341  0.14655624
  -0.16328368]
 [ 0.03625324  0.0511794   0.12720039 ..., -0.243067   -0.05477861
   0.13168955]
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   0.19103136]
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 [-0.19379377 -0.17911654 -0.11335137 ...,  0.10916066 -0.05247468
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  -0.23421124]
 [ 0.06258514 -0.0367588  -0.07740281 ...,  0.03874487  0.221052
   0.20475104]]
Progress: 4.4% ... Training loss: 0.302 ... Validation loss: 0.471[[ 0.29263172]
 [-0.28130538]
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 [ 1.09958209]
 [ 0.41255421]
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 [ 1.07611982]
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[[  4.93512366e-02  -1.32215656e-01   3.93312187e-02 ...,  -1.29299953e-01
    1.45659455e-01  -1.62094238e-01]
 [  3.62135148e-02   5.12118057e-02   1.27307405e-01 ...,  -2.43057148e-01
   -5.48435400e-02   1.31806991e-01]
 [ -8.15197175e-03   2.20733618e-04  -1.23315880e-01 ...,   1.63240994e-01
    5.21447948e-02   1.90978033e-01]
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 [ -1.93576196e-01  -1.79317960e-01  -1.13922008e-01 ...,   1.09103900e-01
   -5.19047686e-02  -2.04163254e-02]
 [ -2.77196351e-01  -2.21573211e-01  -4.69340560e-02 ...,  -1.16113390e-01
   -2.28853374e-03  -2.34091161e-01]
 [  6.29269922e-02  -3.70773094e-02  -7.83644289e-02 ...,   3.86497063e-02
    2.22075164e-01   2.03912921e-01]]
Progress: 4.4% ... Training loss: 0.308 ... Validation loss: 0.476[[ 0.30178815]
 [-0.27381537]
 [-0.79966236]
 [-0.83274035]
 [-0.24492506]
 [ 1.10563639]
 [ 0.41897398]
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 [ 0.12735262]
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 [ 1.08286022]
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[[ 0.05023036 -0.1331272   0.03678827 ..., -0.12954503  0.1480147
  -0.16439385]
 [ 0.03629267  0.0511355   0.12708735 ..., -0.24307956 -0.05462294
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 [-0.19337383 -0.17951765 -0.11437975 ...,  0.10904558 -0.05138155
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  -0.23415867]
 [ 0.06316618 -0.03731403 -0.07913831 ...,  0.03856993  0.22286096
   0.20324413]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.469[[ 0.30756291]
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[[  5.05147826e-02  -1.33379000e-01   3.60772610e-02 ...,  -1.29614671e-01
    1.48740284e-01  -1.65142369e-01]
 [  3.63552282e-02   5.10838487e-02   1.26923480e-01 ...,  -2.43093892e-01
   -5.44551544e-02   1.31471776e-01]
 [ -8.06865423e-03   1.01763809e-04  -1.23587144e-01 ...,   1.63247251e-01
    5.23452076e-02   1.90989008e-01]
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 [ -1.93296970e-01  -1.79588263e-01  -1.14555363e-01 ...,   1.09024394e-01
   -5.11149318e-02  -2.11524866e-02]
 [ -2.77586202e-01  -2.21228455e-01  -4.59081522e-02 ...,  -1.16010767e-01
   -3.36778576e-03  -2.33132806e-01]
 [  6.32658266e-02  -3.74208424e-02  -7.94299436e-02 ...,   3.85413456e-02
    2.23192357e-01   2.02902010e-01]]
Progress: 4.5% ... Training loss: 0.308 ... Validation loss: 0.476[[ 0.29941302]
 [-0.27787614]
 [-0.80333059]
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 [ 1.10523039]
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[[ 0.05004034 -0.13294742  0.03739823 ..., -0.12949305  0.14731374
  -0.16399673]
 [ 0.03640761  0.05103838  0.12678572 ..., -0.24310467 -0.05432923
   0.13133673]
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   0.18931168]
 ..., 
 [-0.19311978 -0.17974935 -0.11500019 ...,  0.10899115 -0.05077885
  -0.02156217]
 [-0.27777406 -0.22106581 -0.04542824 ..., -0.1159674  -0.00386537
  -0.23270504]
 [ 0.06293562 -0.03712505 -0.07866017 ...,  0.03861288  0.22240213
   0.20369492]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.466[[ 0.3018301 ]
 [-0.27586554]
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[[ 0.04971965 -0.13268261  0.03820169 ..., -0.12941712  0.14660174
  -0.16332055]
 [ 0.03640851  0.05103855  0.12678106 ..., -0.24310417 -0.0543286
   0.13133763]
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   0.19002742]
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 [-0.19304916 -0.17981176 -0.1151518  ...,  0.10897327 -0.05060036
  -0.02172359]
 [-0.27807363 -0.22078748 -0.04465073 ..., -0.1158881  -0.00463511
  -0.23195443]
 [ 0.06292975 -0.03712868 -0.07872628 ...,  0.03861592  0.22248936
   0.20364525]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.466[[ 0.30123336]
 [-0.27572981]
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[[ 0.04943671 -0.13239788  0.03911912 ..., -0.12934371  0.14594581
  -0.16233609]
 [ 0.03611957  0.05129766  0.12752197 ..., -0.24303086 -0.05505239
   0.13204711]
 [-0.00916622  0.00104047 -0.12065503 ...,  0.16356545  0.04937395
   0.19403191]
 ..., 
 [-0.19313516 -0.17973741 -0.11487195 ...,  0.10899142 -0.05083257
  -0.02150919]
 [-0.27805158 -0.22080841 -0.04470225 ..., -0.11589569 -0.0045679
  -0.23201183]
 [ 0.0631298  -0.03729434 -0.07922922 ...,  0.03856771  0.22316179
   0.203188  ]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.468[[ 0.30411133]
 [-0.27338888]
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[[ 0.04966937 -0.13261283  0.0385318  ..., -0.12941394  0.14678072
  -0.16294079]
 [ 0.0361501   0.05127124  0.12744383 ..., -0.24303813 -0.05497223
   0.13197512]
 [-0.00888158  0.00073042 -0.12147756 ...,  0.16348092  0.05009338
   0.19320386]
 ..., 
 [-0.19311879 -0.17974569 -0.11489697 ...,  0.10898656 -0.05084714
  -0.02148564]
 [-0.27791767 -0.22092593 -0.04503938 ..., -0.11592541 -0.00427717
  -0.23231261]
 [ 0.06315626 -0.0373204  -0.07934316 ...,  0.03855326  0.22358839
   0.20314006]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.468[[ 0.30714782]
 [-0.27184363]
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 [ 1.11077108]
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[[  5.00129612e-02  -1.32922855e-01   3.77200823e-02 ...,  -1.29505175e-01
    1.47515160e-01  -1.63726223e-01]
 [  3.61068296e-02   5.13149757e-02   1.27567823e-01 ...,  -2.43028007e-01
   -5.50939903e-02   1.32061028e-01]
 [ -7.96975307e-03  -1.25348669e-04  -1.23986151e-01 ...,   1.63255682e-01
    5.25304993e-02   1.91219550e-01]
 ..., 
 [ -1.92868383e-01  -1.79965370e-01  -1.15489817e-01 ...,   1.08928296e-01
   -5.02478292e-02  -2.20391460e-02]
 [ -2.78240684e-01  -2.20635718e-01  -4.41855913e-02 ...,  -1.15851078e-01
   -5.11899930e-03  -2.31511562e-01]
 [  6.36356455e-02  -3.77433132e-02  -8.05798969e-02 ...,   3.84428582e-02
    2.24806955e-01   2.01999075e-01]]
Progress: 4.5% ... Training loss: 0.303 ... Validation loss: 0.466[[ 0.30847319]
 [-0.27096385]
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 [ 1.11373161]
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[[ 0.05046206 -0.13334954  0.0366458  ..., -0.12961828  0.1486657
  -0.16482485]
 [ 0.0363614   0.05109311  0.12695804 ..., -0.24308511 -0.05442928
   0.1314307 ]
 [-0.00703259 -0.00095609 -0.12618571 ...,  0.16302662  0.05506666
   0.18914858]
 ..., 
 [-0.1928076  -0.18002893 -0.11569415 ...,  0.10891278 -0.05014512
  -0.02220107]
 [-0.27846597 -0.22043708 -0.04367813 ..., -0.11580063 -0.00570432
  -0.23099083]
 [ 0.06370539 -0.03779261 -0.08067428 ...,  0.03842946  0.22509572
   0.20184486]]
Progress: 4.5% ... Training loss: 0.304 ... Validation loss: 0.466[[ 0.29762843]
 [-0.28065833]
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Progress: 4.5% ... Training loss: 0.303 ... Validation loss: 0.463[[ 0.30502777]
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[[ 0.05111852 -0.13396196  0.03509098 ..., -0.12982456  0.15024273
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   0.20204497]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.462[[ 0.31451754]
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 [ 0.06433637 -0.03838599 -0.08237673 ...,  0.03828602  0.22701372
   0.20035701]]
Progress: 4.5% ... Training loss: 0.322 ... Validation loss: 0.488[[ 0.30178825]
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[[ 0.05092509 -0.13382671  0.03560593 ..., -0.12980901  0.14960002
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   0.20064342]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.458[[ 0.29530507]
 [-0.28525526]
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[[ 0.05038616 -0.13332124  0.03702761 ..., -0.12967472  0.14811183
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 [ 0.06436557 -0.03842055 -0.08255119 ...,  0.03827695  0.22742569
   0.20030054]]
Progress: 4.5% ... Training loss: 0.311 ... Validation loss: 0.473[[ 0.30622649]
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[[ 0.05054611 -0.13351397  0.03657944 ..., -0.12973186  0.14859652
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 [ 0.06493045 -0.03901784 -0.08422204 ...,  0.03810675  0.22909555
   0.19866899]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.461[[ 0.30078171]
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   0.19821722]]
Progress: 4.5% ... Training loss: 0.300 ... Validation loss: 0.459[[ 0.30514439]
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   0.19919857]]
Progress: 4.6% ... Training loss: 0.302 ... Validation loss: 0.457[[ 0.29847291]
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   0.19877243]]
Progress: 4.6% ... Training loss: 0.302 ... Validation loss: 0.460[[ 0.30567322]
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[[ 0.05037773 -0.13335     0.03731856 ..., -0.12971338  0.14813728
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   0.19731857]]
Progress: 4.6% ... Training loss: 0.302 ... Validation loss: 0.459[[ 0.30006237]
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   0.19855567]]
Progress: 4.6% ... Training loss: 0.301 ... Validation loss: 0.460[[ 0.30394715]
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[[ 0.05064954 -0.13358422  0.03687873 ..., -0.12978246  0.14870539
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   0.1989699 ]]
Progress: 4.6% ... Training loss: 0.299 ... Validation loss: 0.460[[ 0.30171729]
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[[ 0.05093685 -0.133892    0.03603257 ..., -0.12985786  0.14976275
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   0.19995125]]
Progress: 4.6% ... Training loss: 0.301 ... Validation loss: 0.460[[ 0.3100864 ]
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[[ 0.05187939 -0.1347923   0.03359743 ..., -0.13009447  0.15214694
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   0.19907583]]
Progress: 4.6% ... Training loss: 0.308 ... Validation loss: 0.465[[ 0.29919616]
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[[ 0.05069156 -0.1337278   0.03681496 ..., -0.12984932  0.14901694
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   0.19971542]]
Progress: 4.6% ... Training loss: 0.303 ... Validation loss: 0.462[[ 0.29733087]
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[[ 0.05069236 -0.13373557  0.03683184 ..., -0.12985068  0.14904638
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   0.19972089]]
Progress: 4.6% ... Training loss: 0.307 ... Validation loss: 0.465[[ 0.2987247 ]
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 [ 0.06415248 -0.03814951 -0.08213202 ...,  0.03831309  0.22800295
   0.20077595]]
Progress: 4.6% ... Training loss: 0.304 ... Validation loss: 0.465[[ 0.31136475]
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[[ 0.05090141 -0.13389404  0.03640465 ..., -0.12990013  0.14965118
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   0.20006152]]
Progress: 4.6% ... Training loss: 0.310 ... Validation loss: 0.476[[ 0.29040314]
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[[ 0.04970323 -0.13281366  0.03957211 ..., -0.12965398  0.1465538
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   0.20191142]]
Progress: 4.6% ... Training loss: 0.329 ... Validation loss: 0.489[[ 0.29732572]
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[[ 0.04965553 -0.13275065  0.03970623 ..., -0.1296439   0.1463821
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   0.20186473]]
Progress: 4.6% ... Training loss: 0.305 ... Validation loss: 0.471[[ 0.3051032 ]
 [-0.27952315]
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[[ 0.05081581 -0.13388173  0.03680673 ..., -0.12994069  0.14929933
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   0.20209364]]
Progress: 4.6% ... Training loss: 0.300 ... Validation loss: 0.466[[ 0.30317884]
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[[ 0.05080852 -0.1338857   0.03686562 ..., -0.12994568  0.14929855
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   0.20100221]]
Progress: 4.6% ... Training loss: 0.299 ... Validation loss: 0.464[[ 0.31386641]
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[[ 0.05184525 -0.13488721  0.03416037 ..., -0.13019515  0.15199678
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   0.20011899]]
Progress: 4.7% ... Training loss: 0.317 ... Validation loss: 0.487[[ 0.28886431]
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[[ 0.05026701 -0.13350132  0.03808831 ..., -0.12987449  0.14803829
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   0.20156539]]
Progress: 4.7% ... Training loss: 0.344 ... Validation loss: 0.504[[ 0.31389369]
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   0.2006443 ]]
Progress: 4.7% ... Training loss: 0.315 ... Validation loss: 0.491[[ 0.29772676]
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[[ 0.05109708 -0.13444888  0.03569082 ..., -0.13019531  0.15030383
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   0.20075833]]
Progress: 4.7% ... Training loss: 0.307 ... Validation loss: 0.469[[ 0.3088837 ]
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[[ 0.05154224 -0.1348926   0.03455366 ..., -0.13031879  0.15160896
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   0.20015988]]
Progress: 4.7% ... Training loss: 0.302 ... Validation loss: 0.468[[ 0.29786169]
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[[ 0.05102302 -0.13442765  0.03593075 ..., -0.1302193   0.1503099
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   0.20087547]]
Progress: 4.7% ... Training loss: 0.308 ... Validation loss: 0.464[[ 0.3020604 ]
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[[ 0.0505225  -0.1339146   0.03734702 ..., -0.13008991  0.14920564
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   0.20098439]]
Progress: 4.7% ... Training loss: 0.300 ... Validation loss: 0.461[[ 0.29989497]
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[[ 0.05054997 -0.13394736  0.03733962 ..., -0.1300945   0.14937217
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   0.20182517]]
Progress: 4.7% ... Training loss: 0.303 ... Validation loss: 0.462[[ 0.30523448]
 [-0.28350593]
 [-0.79542649]
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 [ 1.12255803]
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[[  5.09736333e-02  -1.34335239e-01   3.62684761e-02 ...,  -1.30183733e-01
    1.50492568e-01  -1.66425409e-01]
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   -5.42145025e-02   1.31444541e-01]
 [ -9.29312261e-03   1.03790335e-04  -1.20611476e-01 ...,   1.63063176e-01
    5.08432791e-02   1.96706199e-01]
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   -4.89387693e-02  -2.45344872e-02]
 [ -2.77042058e-01  -2.21933671e-01  -4.77598812e-02 ...,  -1.16255750e-01
   -2.21369376e-03  -2.34830717e-01]
 [  6.36126995e-02  -3.76446171e-02  -8.10929748e-02 ...,   3.83913559e-02
    2.28033653e-01   2.02075417e-01]]
Progress: 4.7% ... Training loss: 0.299 ... Validation loss: 0.460[[ 0.30816313]
 [-0.28081954]
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 [ 1.12545319]
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[[ 0.05101677 -0.13433925  0.03632391 ..., -0.13018411  0.1504088
  -0.1664758 ]
 [ 0.03627211  0.05115216  0.12702606 ..., -0.24308368 -0.05444243
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 [-0.19185961 -0.18110045 -0.11811098 ...,  0.10853848 -0.04841681
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  -0.23594949]
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   0.2027331 ]]
Progress: 4.7% ... Training loss: 0.303 ... Validation loss: 0.464[[ 0.30662023]
 [-0.28370418]
 [-0.79471723]
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 [ 1.12445432]
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[[ 0.05115825 -0.13438095  0.03621005 ..., -0.13019879  0.15037108
  -0.16665468]
 [ 0.03619704  0.05121059  0.12720668 ..., -0.2430662  -0.05459001
   0.13183073]
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 [-0.191608   -0.18131383 -0.11871813 ...,  0.10848316 -0.04779357
  -0.02567605]
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  -0.23621974]
 [ 0.06348604 -0.03751268 -0.08073296 ...,  0.03842643  0.22783859
   0.20242964]]
Progress: 4.7% ... Training loss: 0.301 ... Validation loss: 0.460[[ 0.30367224]
 [-0.28686662]
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 [ 0.41894842]
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[[ 0.05091883 -0.13416578  0.03699052 ..., -0.13014043  0.14974758
  -0.16600378]
 [ 0.0360399   0.05134198  0.12752837 ..., -0.24303934 -0.05490331
   0.13220359]
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  -0.23637688]
 [ 0.06272089 -0.03677354 -0.07867405 ...,  0.03860461  0.22595925
   0.20439938]]
Progress: 4.7% ... Training loss: 0.299 ... Validation loss: 0.459[[ 0.30275717]
 [-0.28722027]
 [-0.79810951]
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 [ 1.12287169]
 [ 0.41756788]
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[[ 0.05108413 -0.13428919  0.03673051 ..., -0.13017753  0.15012895
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 [ 0.03587638  0.0514982   0.12794362 ..., -0.24300146 -0.05529371
   0.13262619]
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   0.20393968]]
Progress: 4.7% ... Training loss: 0.299 ... Validation loss: 0.461[[ 0.30383417]
 [-0.28593002]
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[[  5.06584935e-02  -1.33872373e-01   3.81549358e-02 ...,  -1.30089142e-01
    1.48955671e-01  -1.65424265e-01]
 [  3.58906608e-02   5.14857574e-02   1.27903508e-01 ...,  -2.43004389e-01
   -5.52564959e-02   1.32589484e-01]
 [ -8.72860232e-03  -7.39944165e-04  -1.22072420e-01 ...,   1.62846710e-01
    5.20522696e-02   1.95839620e-01]
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 [ -1.92256706e-01  -1.80716520e-01  -1.17011327e-01 ...,   1.08627357e-01
   -4.94913002e-02  -2.40799389e-02]
 [ -2.76053741e-01  -2.22817049e-01  -5.02760821e-02 ...,  -1.16466168e-01
    7.42648268e-05  -2.37208752e-01]
 [  6.28434649e-02  -3.68536903e-02  -7.89412504e-02 ...,   3.85811496e-02
    2.26333770e-01   2.04120026e-01]]
Progress: 4.7% ... Training loss: 0.300 ... Validation loss: 0.462[[ 0.29725624]
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[[ 0.05013372 -0.13338087  0.03958816 ..., -0.12996788  0.1476857
  -0.16414478]
 [ 0.0361115   0.05126071  0.12729029 ..., -0.2430585  -0.05462555
   0.13206027]
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 [-0.19253777 -0.18044972 -0.11633309 ...,  0.10869469 -0.05019735
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  -0.23741409]
 [ 0.06252875 -0.0365561  -0.07809463 ...,  0.03865368  0.22567911
   0.20489332]]
Progress: 4.7% ... Training loss: 0.307 ... Validation loss: 0.467[[ 0.30946107]
 [-0.28159201]
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 [ 1.12806142]
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[[ 0.05144158 -0.13468138  0.03608617 ..., -0.13030476  0.15100131
  -0.16737711]
 [ 0.03604734  0.051329    0.12746687 ..., -0.24304458 -0.0547886
   0.13222921]
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 [-0.19259492 -0.1804003  -0.11619113 ...,  0.10870632 -0.05043351
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   0.20390285]]
Progress: 4.8% ... Training loss: 0.306 ... Validation loss: 0.474[[ 0.30921097]
 [-0.28132542]
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[[  5.20350889e-02  -1.35219689e-01   3.48170852e-02 ...,  -1.30430386e-01
    1.52371905e-01  -1.68673222e-01]
 [  3.61110112e-02   5.12709615e-02   1.27303633e-01 ...,  -2.43058601e-01
   -5.46210244e-02   1.32083501e-01]
 [ -9.44271843e-03  -9.55345754e-05  -1.19881015e-01 ...,   1.63015736e-01
    4.96317341e-02   1.97887077e-01]
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 [ -1.92557506e-01  -1.80431482e-01  -1.16246724e-01 ...,   1.08697615e-01
   -5.03500682e-02  -2.33053798e-02]
 [ -2.76083872e-01  -2.22786344e-01  -5.01525616e-02 ...,  -1.16467203e-01
    4.30928482e-05  -2.37067345e-01]
 [  6.29140976e-02  -3.69383504e-02  -7.91401818e-02 ...,   3.85577978e-02
    2.27084314e-01   2.03914876e-01]]
Progress: 4.8% ... Training loss: 0.305 ... Validation loss: 0.473[[ 0.2970776 ]
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[[ 0.05066    -0.1339354   0.03833488 ..., -0.13012299  0.14885761
  -0.16540927]
 [ 0.03598032  0.05139527  0.12766053 ..., -0.24302852 -0.05495136
   0.13231973]
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 [-0.19280186 -0.18022378 -0.11561703 ...,  0.10874985 -0.05096772
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  -0.23662839]
 [ 0.06272969 -0.03675796 -0.07878134 ...,  0.03860416  0.22677825
   0.20441096]]
Progress: 4.8% ... Training loss: 0.307 ... Validation loss: 0.465[[ 0.30582813]
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[[ 0.05123812 -0.13449905  0.03677277 ..., -0.13027263  0.1505353
  -0.16675238]
 [ 0.03573744  0.05165176  0.12836153 ..., -0.24296757 -0.05555692
   0.13300685]
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 [-0.19272945 -0.18029513 -0.11584108 ...,  0.10872938 -0.05080113
  -0.0229994 ]
 [-0.27589817 -0.22298024 -0.05061686 ..., -0.11651984  0.0004932
  -0.23758874]
 [ 0.06272312 -0.0367497  -0.07877697 ...,  0.03861241  0.22685594
   0.20442313]]
Progress: 4.8% ... Training loss: 0.300 ... Validation loss: 0.460[[ 0.31202076]
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[[  5.14788005e-02  -1.34725530e-01   3.62223058e-02 ...,  -1.30323247e-01
    1.51017265e-01  -1.67201958e-01]
 [  3.57604158e-02   5.16258899e-02   1.28292989e-01 ...,  -2.42974396e-01
   -5.54862171e-02   1.32950887e-01]
 [ -9.14848664e-03  -5.64256089e-04  -1.20854892e-01 ...,   1.62896979e-01
    5.05261127e-02   1.97020090e-01]
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 [ -1.92497808e-01  -1.80511451e-01  -1.16416461e-01 ...,   1.08678204e-01
   -5.02581649e-02  -2.35521673e-02]
 [ -2.76049737e-01  -2.22835264e-01  -5.02243203e-02 ...,  -1.16485140e-01
    1.19057508e-04  -2.37214599e-01]
 [  6.25033589e-02  -3.65324593e-02  -7.82014715e-02 ...,   3.86666134e-02
    2.26309069e-01   2.04975491e-01]]
Progress: 4.8% ... Training loss: 0.307 ... Validation loss: 0.472[[ 0.3014449 ]
 [-0.29091341]
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[[  5.09757595e-02  -1.34249917e-01   3.77330243e-02 ...,  -1.30219080e-01
    1.49391114e-01  -1.65867026e-01]
 [  3.56505266e-02   5.17226475e-02   1.28550041e-01 ...,  -2.42949539e-01
   -5.57771343e-02   1.33223592e-01]
 [ -9.93913044e-03   1.14024763e-04  -1.18651325e-01 ...,   1.63055199e-01
    4.84123356e-02   1.99091552e-01]
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 [ -1.92594558e-01  -1.80425277e-01  -1.16224448e-01 ...,   1.08699308e-01
   -5.05149954e-02  -2.33081719e-02]
 [ -2.76098627e-01  -2.22792013e-01  -5.00877884e-02 ...,  -1.16474958e-01
   -4.18144658e-05  -2.37048584e-01]
 [  6.23219962e-02  -3.63539715e-02  -7.77155672e-02 ...,   3.87088366e-02
    2.25834198e-01   2.05441654e-01]]
Progress: 4.8% ... Training loss: 0.301 ... Validation loss: 0.461[[ 0.30855019]
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[[ 0.05110215 -0.13436831  0.03745513 ..., -0.13025327  0.14975355
  -0.16619051]
 [ 0.03573134  0.05164609  0.12834005 ..., -0.24296918 -0.05555688
   0.13300691]
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   0.20192073]
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 [-0.19262687 -0.18040165 -0.11611279 ...,  0.10870458 -0.05063277
  -0.02327124]
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  -0.23747905]
 [ 0.06265657 -0.03668585 -0.07859902 ...,  0.03862644  0.22677868
   0.20452306]]
Progress: 4.8% ... Training loss: 0.299 ... Validation loss: 0.466[[ 0.30265912]
 [-0.29023601]
 [-0.80347281]
 [-0.83759028]
 [-0.25356301]
 [ 1.12405083]
 [ 0.41755106]
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 [ 0.72228071]
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 [ 0.03335938]
 [ 1.73990716]
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[[  5.07076734e-02  -1.33972671e-01   3.85242138e-02 ...,  -1.30162185e-01
    1.48715900e-01  -1.65232421e-01]
 [  3.56716697e-02   5.17013775e-02   1.28495612e-01 ...,  -2.42955722e-01
   -5.56849720e-02   1.33162049e-01]
 [ -1.10175352e-02   1.07727482e-03  -1.15756985e-01 ...,   1.63296391e-01
    4.56920416e-02   2.01760045e-01]
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 [ -1.92814335e-01  -1.80231434e-01  -1.15619923e-01 ...,   1.08741638e-01
   -5.11046972e-02  -2.28390311e-02]
 [ -2.76076659e-01  -2.22816677e-01  -5.01844649e-02 ...,  -1.16482075e-01
   -1.02854351e-05  -2.37161448e-01]
 [  6.24790927e-02  -3.65149194e-02  -7.81319188e-02 ...,   3.86705797e-02
    2.26415682e-01   2.04974585e-01]]
Progress: 4.8% ... Training loss: 0.300 ... Validation loss: 0.461[[ 0.30443466]
 [-0.28889515]
 [-0.80200251]
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 [-0.25127559]
 [ 1.12486357]
 [ 0.41811839]
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[[  5.08130820e-02  -1.34101311e-01   3.82223824e-02 ...,  -1.30199991e-01
    1.49176512e-01  -1.65362207e-01]
 [  3.56915039e-02   5.16808760e-02   1.28403577e-01 ...,  -2.42963489e-01
   -5.55909005e-02   1.33163662e-01]
 [ -1.16211874e-02   1.63809786e-03  -1.14101912e-01 ...,   1.63434730e-01
    4.38893800e-02   2.03297438e-01]
 ..., 
 [ -1.92708491e-01  -1.80328942e-01  -1.15884520e-01 ...,   1.08715018e-01
   -5.08301039e-02  -2.30995211e-02]
 [ -2.76135035e-01  -2.22764204e-01  -5.00048293e-02 ...,  -1.16470524e-01
   -1.59482727e-04  -2.36978717e-01]
 [  6.24282440e-02  -3.64392286e-02  -7.79663334e-02 ...,   3.86833689e-02
    2.26298921e-01   2.05152794e-01]]
Progress: 4.8% ... Training loss: 0.299 ... Validation loss: 0.462[[ 0.30958327]
 [-0.28404267]
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 [ 1.12966258]
 [ 0.42254006]
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 [ 0.2822972 ]
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 [ 1.09589522]
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 [ 1.74834107]
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 [-0.78219023]]
[[  5.12750929e-02  -1.34579872e-01   3.70264505e-02 ...,  -1.30315151e-01
    1.50308824e-01  -1.66430515e-01]
 [  3.58962387e-02   5.14866498e-02   1.27871169e-01 ...,  -2.43012355e-01
   -5.50642780e-02   1.32624289e-01]
 [ -1.16045700e-02   1.59924334e-03  -1.14132988e-01 ...,   1.63417172e-01
    4.42718272e-02   2.03172697e-01]
 ..., 
 [ -1.92527631e-01  -1.80515477e-01  -1.16339842e-01 ...,   1.08675431e-01
   -5.05077762e-02  -2.36006329e-02]
 [ -2.76156045e-01  -2.22749733e-01  -4.99466460e-02 ...,  -1.16464474e-01
   -2.06023240e-04  -2.36902137e-01]
 [  6.23677040e-02  -3.63778479e-02  -7.77540407e-02 ...,   3.87018357e-02
    2.26234505e-01   2.05320663e-01]]
Progress: 4.8% ... Training loss: 0.300 ... Validation loss: 0.469[[ 0.30230847]
 [-0.29165521]
 [-0.80381324]
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 [-0.25483665]
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 [ 1.09004863]
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 [-0.78956779]]
[[  5.08958490e-02  -1.34238144e-01   3.79948731e-02 ...,  -1.30237460e-01
    1.49286784e-01  -1.65483726e-01]
 [  3.58775971e-02   5.15039160e-02   1.27917024e-01 ...,  -2.43007866e-01
   -5.51160160e-02   1.32660771e-01]
 [ -1.15361714e-02   1.53019764e-03  -1.14261385e-01 ...,   1.63397688e-01
    4.41089211e-02   2.03318605e-01]
 ..., 
 [ -1.92501960e-01  -1.80538293e-01  -1.16446939e-01 ...,   1.08668137e-01
   -5.04909017e-02  -2.37198530e-02]
 [ -2.76154235e-01  -2.22750703e-01  -4.98844909e-02 ...,  -1.16467794e-01
   -2.69667544e-04  -2.36858905e-01]
 [  6.20223889e-02  -3.60561343e-02  -7.68506522e-02 ...,   3.87825484e-02
    2.25370314e-01   2.06175515e-01]]
Progress: 4.8% ... Training loss: 0.302 ... Validation loss: 0.462[[ 0.32037494]
 [-0.27600598]
 [-0.78967252]
 [-0.82628659]
 [-0.23939012]
 [ 1.14094161]
 [ 0.43356839]
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 [ 0.13270763]
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[[ 0.05214967 -0.13550114  0.03469157 ..., -0.13055179  0.15255335
  -0.1687849 ]
 [ 0.03606211  0.05133582  0.12745065 ..., -0.24305475 -0.0545824
   0.13218907]
 [-0.01050984  0.00050601 -0.11692701 ...,  0.16313637  0.04709829
   0.20064615]
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 [-0.19219191 -0.18083478 -0.11727108 ...,  0.10859696 -0.04978851
  -0.02447593]
 [-0.27622232 -0.22268482 -0.04970984 ..., -0.11644823 -0.00045571
  -0.23670775]
 [ 0.06340815 -0.03740923 -0.08050499 ...,  0.038437    0.22905727
   0.20256694]]
Progress: 4.8% ... Training loss: 0.332 ... Validation loss: 0.500[[ 0.29838301]
 [-0.29632076]
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 [-0.84466834]
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 [ 0.41391066]
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[[ 0.05041099 -0.13400174  0.03897675 ..., -0.13023822  0.14819129
  -0.16452926]
 [ 0.03606211  0.05133582  0.12745065 ..., -0.24305475 -0.0545824
   0.13218907]
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   0.2044263 ]
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 [-0.1930922  -0.18007347 -0.11514687 ...,  0.10875416 -0.0520531
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  -0.23635668]
 [ 0.06323377 -0.0372635  -0.08009241 ...,  0.03847027  0.22870908
   0.20296259]]
Progress: 4.8% ... Training loss: 0.313 ... Validation loss: 0.467[[ 0.31137146]
 [-0.28390425]
 [-0.79789603]
 [-0.83169476]
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 [ 1.13159916]
 [ 0.42644532]
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[[  5.06811984e-02  -1.34263362e-01   3.84120512e-02 ...,  -1.30311570e-01
    1.48809817e-01  -1.65211447e-01]
 [  3.60333139e-02   5.13648844e-02   1.27527212e-01 ...,  -2.43046890e-01
   -5.46609443e-02   1.32267181e-01]
 [ -1.21936284e-02   2.02933128e-03  -1.12363093e-01 ...,   1.63448960e-01
    4.27172746e-02   2.05129001e-01]
 ..., 
 [ -1.92775319e-01  -1.80386250e-01  -1.15970410e-01 ...,   1.08676374e-01
   -5.13555799e-02  -2.32068578e-02]
 [ -2.76125942e-01  -2.22793348e-01  -5.00139581e-02 ...,  -1.16489897e-01
   -1.99278698e-04  -2.36939341e-01]
 [  6.36154835e-02  -3.76537796e-02  -8.10784096e-02 ...,   3.83661371e-02
    2.29763513e-01   2.01880689e-01]]
Progress: 4.8% ... Training loss: 0.301 ... Validation loss: 0.463[[ 0.30389095]
 [-0.29124153]
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 [ 1.12657813]
 [ 0.42011903]
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[[ 0.05042127 -0.13404677  0.03907161 ..., -0.13024911  0.14831826
  -0.16465345]
 [ 0.03607637  0.05131718  0.12738138 ..., -0.24305591 -0.05443236
   0.13213239]
 [-0.01068469  0.00060108 -0.11625002 ...,  0.1631355   0.04671032
   0.20165042]
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 [-0.19296984 -0.18021539 -0.11544653 ...,  0.10871745 -0.0518435
  -0.02278961]
 [-0.27623026 -0.22269612 -0.04976314 ..., -0.11646822 -0.00041519
  -0.23674567]
 [ 0.06336333 -0.03740523 -0.0804277  ...,  0.03843952  0.22920011
   0.20255247]]
Progress: 4.8% ... Training loss: 0.301 ... Validation loss: 0.456[[ 0.30492895]
 [-0.29025037]
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[[  5.02110882e-02  -1.33840945e-01   3.96955669e-02 ...,  -1.30199441e-01
    1.47720544e-01  -1.63987099e-01]
 [  3.60131213e-02   5.13780204e-02   1.27547835e-01 ...,  -2.43040891e-01
   -5.46013162e-02   1.32297289e-01]
 [ -1.18583483e-02   1.74598286e-03  -1.12986657e-01 ...,   1.63404282e-01
    4.34879850e-02   2.05001907e-01]
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 [ -1.93176099e-01  -1.80019190e-01  -1.14923148e-01 ...,   1.08766691e-01
   -5.23890302e-02  -2.22788857e-02]
 [ -2.76108192e-01  -2.22809631e-01  -5.00851198e-02 ...,  -1.16495265e-01
   -9.24096767e-05  -2.37050977e-01]
 [  6.30630347e-02  -3.71319495e-02  -7.96567392e-02 ...,   3.85136968e-02
    2.28450945e-01   2.03344143e-01]]
Progress: 4.9% ... Training loss: 0.300 ... Validation loss: 0.458[[ 0.30924219]
 [-0.28881256]
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[[ 0.05154197 -0.13520081  0.03605226 ..., -0.13053576  0.15099775
  -0.16721463]
 [ 0.03585454  0.05153255  0.12795885 ..., -0.24300509 -0.05498236
   0.1327214 ]
 [-0.01197048  0.00182183 -0.11278138 ...,  0.16342253  0.04327712
   0.20548832]
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 [-0.19292399 -0.18027643 -0.11556123 ...,  0.10870612 -0.05187715
  -0.02285631]
 [-0.27614922 -0.22278429 -0.04991636 ..., -0.11648908 -0.00029588
  -0.23686889]
 [ 0.06376414 -0.03783436 -0.08161672 ...,  0.03833234  0.23045096
   0.20157376]]
Progress: 4.9% ... Training loss: 0.299 ... Validation loss: 0.458[[ 0.31226168]
 [-0.28876048]
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[[ 0.05152497 -0.13519029  0.036073   ..., -0.13053416  0.15115814
  -0.16708435]
 [ 0.03591057  0.05147982  0.12781247 ..., -0.24301805 -0.05483256
   0.13260928]
 [-0.01184024  0.00165666 -0.11321342 ...,  0.16338964  0.04367461
   0.20519506]
 ..., 
 [-0.19295602 -0.18023845 -0.11550056 ...,  0.10871603 -0.05199374
  -0.02277419]
 [-0.27627666 -0.22266288 -0.04958302 ..., -0.11646902 -0.00055632
  -0.23657994]
 [ 0.06425182 -0.03828078 -0.08285815 ...,  0.03822157  0.23183315
   0.20036403]]
Progress: 4.9% ... Training loss: 0.300 ... Validation loss: 0.459[[ 0.30664679]
 [-0.29307593]
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 [ 1.12705905]
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[[ 0.05125235 -0.13496595  0.03684915 ..., -0.13046831  0.15041815
  -0.16659595]
 [ 0.03570077  0.05167809  0.12835113 ..., -0.24297103 -0.05537324
   0.13306217]
 [-0.0110573   0.00084955 -0.11540091 ...,  0.1632002   0.04584288
   0.20327165]
 ..., 
 [-0.1931609  -0.18004772 -0.11500445 ...,  0.10875852 -0.05252048
  -0.02228431]
 [-0.27668063 -0.22229633 -0.04855838 ..., -0.11638384 -0.00160177
  -0.23564112]
 [ 0.06420138 -0.03823006 -0.08269088 ...,  0.03823146  0.23163092
   0.20043326]]
Progress: 4.9% ... Training loss: 0.299 ... Validation loss: 0.455[[ 0.31876668]
 [-0.28380524]
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 [ 1.13514899]
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[[ 0.05197404 -0.13569081  0.03499597 ..., -0.1306476   0.15213951
  -0.16848409]
 [ 0.03565977  0.05171734  0.12844992 ..., -0.24296143 -0.05548274
   0.13317027]
 [-0.01105455  0.00080379 -0.115312   ...,  0.16318898  0.04593273
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   0.19916742]]
Progress: 4.9% ... Training loss: 0.309 ... Validation loss: 0.475[[ 0.30158786]
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 [-0.80756875]
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 [ 1.12312007]
 [ 0.41395567]
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[[ 0.05090641 -0.13469692  0.03782585 ..., -0.13044449  0.14931514
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   0.19949313]]
Progress: 4.9% ... Training loss: 0.312 ... Validation loss: 0.466[[ 0.32191285]
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[[  5.22024462e-02  -1.36022806e-01   3.43280559e-02 ...,  -1.30782988e-01
    1.52568606e-01  -1.69215340e-01]
 [  3.54655196e-02   5.19084321e-02   1.28959015e-01 ...,  -2.42914324e-01
   -5.60088463e-02   1.33648612e-01]
 [ -1.02027160e-02  -1.11012529e-04  -1.17497997e-01 ...,   1.62925630e-01
    4.80341713e-02   2.01053704e-01]
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 [ -2.76343524e-01  -2.22626251e-01  -4.93709187e-02 ...,  -1.16465427e-01
   -8.71604689e-04  -2.36495385e-01]
 [  6.43031664e-02  -3.83130450e-02  -8.29230960e-02 ...,   3.82103111e-02
    2.32058773e-01   2.00195822e-01]]
Progress: 4.9% ... Training loss: 0.320 ... Validation loss: 0.483[[ 0.31255304]
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[[ 0.05215876 -0.13597374  0.03450807 ..., -0.13078092  0.15265119
  -0.1690499 ]
 [ 0.03539636  0.05196732  0.12912094 ..., -0.24290105 -0.05615901
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  -0.23636968]
 [ 0.06431375 -0.03829533 -0.0828743  ...,  0.03821375  0.23220123
   0.20021915]]
Progress: 4.9% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.31455534]
 [-0.28799658]
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[[ 0.05218596 -0.13602016  0.03458442 ..., -0.13078772  0.15265546
  -0.16893765]
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  -0.23635526]
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   0.20056713]]
Progress: 4.9% ... Training loss: 0.301 ... Validation loss: 0.457[[ 0.31090185]
 [-0.29050152]
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[[ 0.05148141 -0.13535546  0.03638505 ..., -0.13063006  0.15089512
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   0.20065369]]
Progress: 4.9% ... Training loss: 0.299 ... Validation loss: 0.455[[ 0.30379911]
 [-0.29612345]
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[[ 0.05008387 -0.13401199  0.04020344 ..., -0.13030222  0.14739994
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   0.2004748 ]]
Progress: 4.9% ... Training loss: 0.311 ... Validation loss: 0.469[[ 0.31529954]
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[[  5.13656684e-02  -1.35242188e-01   3.69591889e-02 ...,  -1.30621023e-01
    1.50745930e-01  -1.66917236e-01]
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   -5.63419851e-02   1.33990062e-01]
 [ -1.03520639e-02  -4.01400031e-05  -1.16594006e-01 ...,   1.62966229e-01
    4.74752422e-02   2.02102567e-01]
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 [ -1.91615883e-01  -1.81556424e-01  -1.18735144e-01 ...,   1.08363196e-01
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   -2.56827088e-03  -2.34833164e-01]
 [  6.39464888e-02  -3.78924978e-02  -8.18923999e-02 ...,   3.83201853e-02
    2.31762563e-01   2.01219437e-01]]
Progress: 4.9% ... Training loss: 0.301 ... Validation loss: 0.455[[ 0.30586594]
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[[ 0.0500845  -0.13406724  0.04030302 ..., -0.1303531   0.14776987
  -0.16364909]
 [ 0.03517068  0.05217103  0.12971263 ..., -0.24285651 -0.05661829
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 [-0.19176209 -0.18142394 -0.11828814 ...,  0.10839406 -0.0494165
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 [ 0.06351293 -0.03749091 -0.08093612 ...,  0.03841445  0.2309634
   0.20226199]]
Progress: 4.9% ... Training loss: 0.305 ... Validation loss: 0.462[[ 0.3242677 ]
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[[ 0.05157233 -0.13558208  0.03638623 ..., -0.13073685  0.15157616
  -0.16750784]
 [ 0.03554393  0.05181141  0.12873291 ..., -0.24294963 -0.05563928
   0.13341097]
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 [-0.19186204 -0.18132973 -0.11800488 ...,  0.10841456 -0.04967573
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 [-0.27717724 -0.22186342 -0.04728966 ..., -0.11630656 -0.00293365
  -0.23451135]
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   0.20031434]]
Progress: 4.9% ... Training loss: 0.322 ... Validation loss: 0.477[[ 0.30723991]
 [-0.29661436]
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[[ 0.05046369 -0.13457364  0.03927628 ..., -0.13054411  0.14850853
  -0.16496762]
 [ 0.0354485   0.05189729  0.12897354 ..., -0.24293304 -0.05589346
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 [-0.19221024 -0.18102094 -0.11716282 ...,  0.10847471 -0.05060516
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  -0.2334774 ]
 [ 0.06438744 -0.0383362  -0.0831658  ...,  0.03820475  0.23321246
   0.19999714]]
Progress: 4.9% ... Training loss: 0.305 ... Validation loss: 0.461[[ 0.32031483]
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[[ 0.05075041 -0.13482511  0.03863862 ..., -0.13060193  0.1490877
  -0.16595302]
 [ 0.03543825  0.05190875  0.1290099  ..., -0.24292951 -0.05593116
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 [-0.19218993 -0.18104797 -0.117217   ...,  0.10846594 -0.05053317
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 [-0.27728703 -0.22179697 -0.04705076 ..., -0.11630217 -0.00330455
  -0.23431682]
 [ 0.06447108 -0.03841362 -0.08340882 ...,  0.03818414  0.23345491
   0.19976723]]
Progress: 5.0% ... Training loss: 0.305 ... Validation loss: 0.464[[ 0.31617246]
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[[ 0.05193643 -0.13593663  0.03556693 ..., -0.13085008  0.15205434
  -0.16866751]
 [ 0.03548598  0.05186823  0.12889117 ..., -0.24293929 -0.05581591
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 [-0.19265538 -0.18063268 -0.11612414 ...,  0.10856133 -0.05179089
  -0.02382524]
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  -0.23436785]
 [ 0.06353422 -0.03755162 -0.08112031 ...,  0.038375    0.23126741
   0.20196477]]
Progress: 5.0% ... Training loss: 0.299 ... Validation loss: 0.456[[ 0.30492919]
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[[ 0.0511752  -0.1352323   0.03745717 ..., -0.13069305  0.15021003
  -0.16686119]
 [ 0.0354518   0.05189662  0.12897633 ..., -0.24293165 -0.05590511
   0.13362279]
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   0.20681474]
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 [-0.19309171 -0.18023345 -0.11503523 ...,  0.10865016 -0.05292139
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  -0.23304292]
 [ 0.06358763 -0.03760405 -0.08126821 ...,  0.0383674   0.23144504
   0.20182716]]
Progress: 5.0% ... Training loss: 0.316 ... Validation loss: 0.472[[ 0.31526639]
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[[ 0.05180089 -0.1358356   0.03596639 ..., -0.13085488  0.15179995
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 [ 0.03557187  0.05177042  0.12864296 ..., -0.24296629 -0.05551553
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 [-0.19318018 -0.18014856 -0.11479798 ...,  0.10867376 -0.05316098
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 [ 0.06364274 -0.0376347  -0.08141172 ...,  0.03836108  0.23171305
   0.20171052]]
Progress: 5.0% ... Training loss: 0.298 ... Validation loss: 0.456[[ 0.32530432]
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[[ 0.0522756  -0.13631534  0.03477219 ..., -0.130964    0.1529962
  -0.1696225 ]
 [ 0.03578261  0.05155235  0.12806031 ..., -0.24301849 -0.05483701
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  -0.23221569]
 [ 0.06390785 -0.03788979 -0.08213663 ...,  0.03830396  0.23248296
   0.20106285]]
Progress: 5.0% ... Training loss: 0.315 ... Validation loss: 0.475[[ 0.30600978]
 [-0.29887804]
 [-0.80749203]
 [-0.84435491]
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 [ 1.12349487]
 [ 0.4148691 ]
 [-0.68033984]
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[[ 0.05053995 -0.13478538  0.03899944 ..., -0.13063692  0.14860694
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  -0.23050138]
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   0.20261796]]
Progress: 5.0% ... Training loss: 0.317 ... Validation loss: 0.476[[ 0.32317764]
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[[ 0.05210125 -0.13638764  0.03478439 ..., -0.13105484  0.15278128
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  -0.23160985]
 [ 0.06340519 -0.03744272 -0.08090288 ...,  0.03839492  0.2313566
   0.20229722]]
Progress: 5.0% ... Training loss: 0.306 ... Validation loss: 0.472[[ 0.31475044]
 [-0.29361691]
 [-0.80261319]
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 [ 1.13323991]
 [ 0.42267446]
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[[ 0.05124196 -0.13560744  0.03698573 ..., -0.13088305  0.1505693
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  -0.23158952]
 [ 0.06258021 -0.03669243 -0.07884995 ...,  0.03857099  0.22949008
   0.20433303]]
Progress: 5.0% ... Training loss: 0.298 ... Validation loss: 0.458[[ 0.31743353]
 [-0.2920138 ]
 [-0.80026977]
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 [ 1.13605352]
 [ 0.42568119]
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[[ 0.05141066 -0.13575438  0.03677121 ..., -0.13091206  0.15086226
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  -0.23191598]
 [ 0.06217347 -0.03629705 -0.07781675 ...,  0.03866947  0.22865056
   0.20539085]]
Progress: 5.0% ... Training loss: 0.297 ... Validation loss: 0.458[[ 0.30735545]
 [-0.300779  ]
 [-0.80784477]
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[[ 0.05019066 -0.1345598   0.04002073 ..., -0.1306313   0.14782426
  -0.16472924]
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 [-0.19276762 -0.18056406 -0.1156967  ...,  0.10855967 -0.05234139
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  -0.23160019]
 [ 0.06208579 -0.03620668 -0.07758805 ...,  0.038684    0.22847366
   0.20558613]]
Progress: 5.0% ... Training loss: 0.311 ... Validation loss: 0.470[[ 0.32510441]
 [-0.28542269]
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[[ 0.05144015 -0.13577526  0.03679832 ..., -0.13093126  0.15116747
  -0.1678393 ]
 [ 0.03625082  0.05112963  0.1268965  ..., -0.24311795 -0.05367686
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  -0.23252577]
 [ 0.06200118 -0.03610079 -0.07733107 ...,  0.03871517  0.22827722
   0.20583738]]
Progress: 5.0% ... Training loss: 0.315 ... Validation loss: 0.469[[ 0.31494405]
 [-0.29540296]
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 [ 1.13796929]
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[[ 0.0509008  -0.13533372  0.03800762 ..., -0.13084384  0.14996445
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 [ 0.03636325  0.05103723  0.12657701 ..., -0.24313704 -0.05337587
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   0.20645727]
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 [-0.19236195 -0.18095115 -0.11665663 ...,  0.10844977 -0.051454   -0.0245482 ]
 [-0.27831549 -0.22096066 -0.04472389 ..., -0.11615267 -0.006078
  -0.23204564]
 [ 0.06149498 -0.03560106 -0.07608861 ...,  0.03882282  0.22729356
   0.2071212 ]]
Progress: 5.0% ... Training loss: 0.298 ... Validation loss: 0.453[[ 0.31877491]
 [-0.29177357]
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 [ 1.14219955]
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[[ 0.05115134 -0.13551004  0.03761495 ..., -0.13089733  0.15047927
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 [-0.19184122 -0.18143641 -0.11788735 ...,  0.10833616 -0.05018291
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  -0.23309472]
 [ 0.0611665  -0.03525965 -0.0752523  ...,  0.03889876  0.22660721
   0.20795795]]
Progress: 5.0% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.31857718]
 [-0.29250034]
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 [ 1.14124114]
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[[ 0.05096636 -0.13534433  0.0382083  ..., -0.13086049  0.1499466
  -0.1666158 ]
 [ 0.03597731  0.05136873  0.12744503 ..., -0.24306382 -0.05426187
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 [-0.1918848  -0.181401   -0.11779095 ...,  0.10834323 -0.0502758
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  -0.23266742]
 [ 0.06127677 -0.03535958 -0.07552276 ...,  0.03887827  0.22692309
   0.20765054]]
Progress: 5.0% ... Training loss: 0.298 ... Validation loss: 0.456[[ 0.32324841]
 [-0.28814162]
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 [-0.83186302]
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 [ 1.14666325]
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[[ 0.05134441 -0.1356615   0.03749939 ..., -0.13094567  0.15076143
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 [ 0.0361137   0.05124336  0.12709932 ..., -0.24309215 -0.05392238
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 [-0.19152876 -0.18173172 -0.11869249 ...,  0.10827025 -0.04942827
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  -0.23260882]
 [ 0.06101903 -0.03512095 -0.07483074 ...,  0.03892511  0.22643039
   0.2081829 ]]
Progress: 5.0% ... Training loss: 0.306 ... Validation loss: 0.462[[ 0.31105445]
 [-0.29945909]
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[[ 0.05043629 -0.1348466   0.03981202 ..., -0.13076662  0.14845217
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 [-0.19181359 -0.18147183 -0.11797611 ...,  0.10832863 -0.05014939
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  -0.23153181]
 [ 0.06046191 -0.03460631 -0.07347835 ...,  0.03903747  0.22510683
   0.20954452]]
Progress: 5.1% ... Training loss: 0.303 ... Validation loss: 0.459[[ 0.32218485]
 [-0.28900649]
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[[ 0.05154026 -0.13592647  0.03707278 ..., -0.13103195  0.1513122
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 [ 0.0361168   0.05122941  0.12704389 ..., -0.24309719 -0.05386375
   0.13193153]
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 ..., 
 [-0.19161193 -0.18166053 -0.11848785 ...,  0.10828538 -0.04960308
  -0.02644269]
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  -0.23261641]
 [ 0.06068331 -0.03481411 -0.07407611 ...,  0.03898517  0.22580809
   0.20897786]]
Progress: 5.1% ... Training loss: 0.303 ... Validation loss: 0.462[[ 0.31254599]
 [-0.29747702]
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[[ 0.05099342 -0.13544896  0.03850973 ..., -0.13093457  0.14985336
  -0.16709896]
 [ 0.0360489   0.05128979  0.12720548 ..., -0.24308399 -0.05402006
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 [-0.19176598 -0.18152233 -0.1180993  ...,  0.10831532 -0.0499958
  -0.02611474]
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  -0.23197568]
 [ 0.06038395 -0.03449718 -0.07327056 ...,  0.03903999  0.22512809
   0.20961787]]
Progress: 5.1% ... Training loss: 0.300 ... Validation loss: 0.457[[ 0.32139161]
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[[  5.24420511e-02  -1.36834535e-01   3.47444267e-02 ...,  -1.31277647e-01
    1.53408265e-01  -1.70664424e-01]
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   -5.41031010e-02   1.32183623e-01]
 [ -1.17746270e-02  -9.42610195e-05  -1.13746211e-01 ...,   1.62696985e-01
    4.60727274e-02   2.06778012e-01]
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 [ -1.91959518e-01  -1.81342507e-01  -1.17599394e-01 ...,   1.08354126e-01
   -5.05285061e-02  -2.56492351e-02]
 [ -2.77986821e-01  -2.21314228e-01  -4.54588113e-02 ...,  -1.16258437e-01
   -5.53726709e-03  -2.33028298e-01]
 [  6.05496745e-02  -3.46425389e-02  -7.37089849e-02 ...,   3.90033338e-02
    2.25702248e-01   2.09167003e-01]]
Progress: 5.1% ... Training loss: 0.302 ... Validation loss: 0.455[[ 0.30960461]
 [-0.29965092]
 [-0.80902601]
 [-0.84533892]
 [-0.26081013]
 [ 1.13902356]
 [ 0.41908515]
 [-0.67975521]
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 [ 0.71997277]
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[[ 0.05168079 -0.13613383  0.03672977 ..., -0.13112183  0.15127498
  -0.16893581]
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 [-0.19214914 -0.18117748 -0.11712943 ...,  0.10839215 -0.05100432
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  -0.23292064]
 [ 0.06059437 -0.03468055 -0.07379912 ...,  0.03899447  0.22585969
   0.20903601]]
Progress: 5.1% ... Training loss: 0.306 ... Validation loss: 0.460[[ 0.31272872]
 [-0.29590773]
 [-0.80424168]
 [-0.84068335]
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 [ 1.14174659]
 [ 0.42328794]
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[[  5.13253927e-02  -1.35736230e-01   3.77152420e-02 ...,  -1.31028909e-01
    1.50353274e-01  -1.68038232e-01]
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   -5.36274211e-02   1.31692986e-01]
 [ -1.17251876e-02  -2.66793135e-04  -1.14237212e-01 ...,   1.62652374e-01
    4.60964183e-02   2.07370135e-01]
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 [ -1.92041264e-01  -1.81285064e-01  -1.17424588e-01 ...,   1.08363597e-01
   -5.07029696e-02  -2.54832965e-02]
 [ -2.77545075e-01  -2.21732213e-01  -4.65975730e-02 ...,  -1.16376638e-01
   -4.49065686e-03  -2.34163579e-01]
 [  6.08741219e-02  -3.49467692e-02  -7.45193412e-02 ...,   3.89231536e-02
    2.26759364e-01   2.08432642e-01]]
Progress: 5.1% ... Training loss: 0.299 ... Validation loss: 0.454[[ 0.31329612]
 [-0.29556332]
 [-0.80389688]
 [-0.83966451]
 [-0.25480215]
 [ 1.14255171]
 [ 0.42420079]
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[[ 0.05191382 -0.13628874  0.03625119 ..., -0.13116205  0.15194759
  -0.16945215]
 [ 0.03614637  0.05119875  0.12696487 ..., -0.24310421 -0.05383145
   0.13186304]
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 [-0.19181357 -0.18149945 -0.11798655 ...,  0.10830879 -0.05015777
  -0.02609079]
 [-0.27779633 -0.22149509 -0.04598399 ..., -0.11631964 -0.00507552
  -0.23352118]
 [ 0.06116375 -0.03521498 -0.07516095 ...,  0.03885686  0.22769677
   0.20777424]]
Progress: 5.1% ... Training loss: 0.299 ... Validation loss: 0.451[[ 0.31138194]
 [-0.29666351]
 [-0.8060298 ]
 [-0.83949302]
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 [ 1.13921591]
 [ 0.42210521]
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[[ 0.05138568 -0.1357833   0.03758377 ..., -0.13105087  0.15067709
  -0.16800129]
 [ 0.03618988  0.05115752  0.12685856 ..., -0.24311351 -0.05372335
   0.13177311]
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   0.21069935]
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 [-0.1919207  -0.18139653 -0.11767278 ...,  0.10833391 -0.05052231
  -0.02581502]
 [-0.27756824 -0.22169825 -0.04655044 ..., -0.11637073 -0.00451955
  -0.23398327]
 [ 0.06107152 -0.03512852 -0.07494731 ...,  0.03887572  0.2276936
   0.20796933]]
Progress: 5.1% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.31945388]
 [-0.29002054]
 [-0.80080471]
 [-0.83222582]
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 [ 1.14389384]
 [ 0.4277253 ]
 [-0.66670286]
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[[ 0.05200035 -0.13640524  0.03603249 ..., -0.13120631  0.15218738
  -0.16961962]
 [ 0.03624323  0.05110731  0.12672012 ..., -0.24312579 -0.05359469
   0.13164702]
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   0.21399876]
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 [-0.19181609 -0.18150262 -0.11789161 ...,  0.1083075  -0.05025357
  -0.0260488 ]
 [-0.27742215 -0.2218242  -0.04690757 ..., -0.11640329 -0.00418163
  -0.23429189]
 [ 0.06124965 -0.03531103 -0.07551897 ...,  0.03882994  0.22835688
   0.20747204]]
Progress: 5.1% ... Training loss: 0.299 ... Validation loss: 0.458[[ 0.3077721 ]
 [-0.2997919 ]
 [-0.81028272]
 [-0.84035296]
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 [ 1.13193416]
 [ 0.41644004]
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[[ 0.05066617 -0.1351835   0.03942117 ..., -0.13093159  0.14881248
  -0.16637795]
 [ 0.03610222  0.05123264  0.12706487 ..., -0.24309636 -0.05394715
   0.13198836]
 [-0.0159077   0.00359298 -0.1036804  ...,  0.16352862  0.03570406
   0.21759734]
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 [-0.19180316 -0.18151908 -0.11792824 ...,  0.10830343 -0.05030401
  -0.02608107]
 [-0.27789877 -0.22139579 -0.04573949 ..., -0.11630401 -0.00533129
  -0.23314545]
 [ 0.06093437 -0.03501334 -0.07473428 ...,  0.03889944  0.22766648
   0.20824708]]
Progress: 5.1% ... Training loss: 0.312 ... Validation loss: 0.469[[ 0.31851072]
 [-0.28971853]
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 [ 1.14176422]
 [ 0.42551641]
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[[ 0.05171566 -0.13617948  0.03680547 ..., -0.13118554  0.15141893
  -0.16914472]
 [ 0.03632113  0.05102292  0.1264914  ..., -0.24314729 -0.05339097
   0.13145177]
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   0.2141802 ]
 ..., 
 [-0.19154889 -0.18176091 -0.11856192 ...,  0.10824172 -0.04955619
  -0.02678554]
 [-0.27777403 -0.22151186 -0.04605748 ..., -0.11633489 -0.00502403
  -0.2334764 ]
 [ 0.06106527 -0.0351168  -0.07507192 ...,  0.0388652   0.22818911
   0.20794072]]
Progress: 5.1% ... Training loss: 0.298 ... Validation loss: 0.461[[ 0.32210196]
 [-0.28694077]
 [-0.79895524]
 [-0.83015835]
 [-0.24667755]
 [ 1.14557656]
 [ 0.43041667]
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[[ 0.0516516  -0.13611528  0.03707142 ..., -0.13116483  0.1508937
  -0.16862238]
 [ 0.03632378  0.05102024  0.12648219 ..., -0.24314777 -0.05338093
   0.13144965]
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   0.21308189]
 ..., 
 [-0.19165401 -0.18166525 -0.1183381  ...,  0.10826353 -0.04981725
  -0.02656361]
 [-0.27792348 -0.22137712 -0.04571009 ..., -0.11630662 -0.00536609
  -0.23314998]
 [ 0.06131877 -0.03534846 -0.07568952 ...,  0.03881068  0.2288217
   0.20733978]]
Progress: 5.1% ... Training loss: 0.303 ... Validation loss: 0.463[[ 0.31120587]
 [-0.29753379]
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 [-0.84003519]
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[[ 0.05071517 -0.13524047  0.03954721 ..., -0.13099204  0.14848345
  -0.16638391]
 [ 0.03615096  0.05117406  0.12690423 ..., -0.24311459 -0.0538038
   0.13186345]
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 [-0.19180319 -0.18153872 -0.1179988  ...,  0.10829008 -0.05023796
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 [-0.2783941  -0.2209652  -0.04454564 ..., -0.11622035 -0.00653426
  -0.23204097]
 [ 0.06128749 -0.03530996 -0.07560311 ...,  0.03881878  0.22888214
   0.20739266]]
Progress: 5.1% ... Training loss: 0.302 ... Validation loss: 0.458[[ 0.32125399]
 [-0.28890603]
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 [ 1.14437307]
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[[ 0.05111845 -0.13567214  0.03841356 ..., -0.13108974  0.14971554
  -0.16736432]
 [ 0.03612286  0.05120118  0.12697695 ..., -0.24310813 -0.05387894
   0.13193219]
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   0.21598797]
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 [-0.19184689 -0.18149954 -0.11786634 ...,  0.10829995 -0.05032194
  -0.0260951 ]
 [-0.27808243 -0.22126557 -0.04531546 ..., -0.11628918 -0.00570905
  -0.23282697]
 [ 0.06192244 -0.03593071 -0.07734997 ...,  0.03868196  0.23064965
   0.20571996]]
Progress: 5.1% ... Training loss: 0.299 ... Validation loss: 0.458[[ 0.32020628]
 [-0.28920261]
 [-0.80108886]
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 [ 1.14776378]
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[[ 0.05168338 -0.13616624  0.03714098 ..., -0.13118677  0.15087989
  -0.16887321]
 [ 0.0361253   0.05119989  0.12696172 ..., -0.24310887 -0.05385771
   0.13192934]
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 [-0.19218474 -0.18119124 -0.11711752 ...,  0.10836386 -0.05117308
  -0.02536654]
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  -0.23356775]
 [ 0.06196479 -0.03595871 -0.07746455 ...,  0.03867965  0.23083112
   0.20561861]]
Progress: 5.1% ... Training loss: 0.299 ... Validation loss: 0.453[[ 0.32820951]
 [-0.28320759]
 [-0.79651103]
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 [-0.24387115]
 [ 1.15658233]
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[[  5.29613895e-02  -1.37359495e-01   3.41594019e-02 ...,  -1.31453650e-01
    1.53926014e-01  -1.72043967e-01]
 [  3.61846698e-02   5.11327005e-02   1.26782143e-01 ...,  -2.43127200e-01
   -5.36004093e-02   1.31797744e-01]
 [ -1.24330116e-02   1.68373885e-04  -1.12132489e-01 ...,   1.62756905e-01
    4.38435668e-02   2.09292312e-01]
 ..., 
 [ -1.91758322e-01  -1.81578421e-01  -1.18131440e-01 ...,   1.08278378e-01
   -5.01369809e-02  -2.63610916e-02]
 [ -2.77766180e-01  -2.21556285e-01  -4.59850765e-02 ...,  -1.16341008e-01
   -5.16033238e-03  -2.33611395e-01]
 [  6.23367013e-02  -3.63042370e-02  -7.84155558e-02 ...,   3.86014566e-02
    2.31785472e-01   2.04682211e-01]]
Progress: 5.2% ... Training loss: 0.320 ... Validation loss: 0.473[[ 0.31896121]
 [-0.29158903]
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[[  5.25787756e-02  -1.36999044e-01   3.50680494e-02 ...,  -1.31387864e-01
    1.52952036e-01  -1.71334655e-01]
 [  3.63850010e-02   5.09595790e-02   1.26297197e-01 ...,  -2.43161521e-01
   -5.30974033e-02   1.31324628e-01]
 [ -1.20415081e-02  -1.92144448e-04  -1.13095418e-01 ...,   1.62681817e-01
    4.47698463e-02   2.08753570e-01]
 ..., 
 [ -1.91850100e-01  -1.81503119e-01  -1.17877410e-01 ...,   1.08288811e-01
   -5.03627075e-02  -2.61433874e-02]
 [ -2.78266123e-01  -2.21123917e-01  -4.47924125e-02 ...,  -1.16259996e-01
   -6.39651942e-03  -2.32512619e-01]
 [  6.17411605e-02  -3.57511127e-02  -7.69019146e-02 ...,   3.87108019e-02
    2.30435549e-01   2.06174271e-01]]
Progress: 5.2% ... Training loss: 0.299 ... Validation loss: 0.448[[ 0.31006093]
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[[ 0.05225895 -0.13665353  0.03597696 ..., -0.13132185  0.15205027
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   0.205605  ]]
Progress: 5.2% ... Training loss: 0.304 ... Validation loss: 0.457[[ 0.31427593]
 [-0.29432214]
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 [ 1.14293187]
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[[ 0.05260317 -0.13696986  0.03523553 ..., -0.13138747  0.15284161
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   0.20548999]]
Progress: 5.2% ... Training loss: 0.297 ... Validation loss: 0.456[[ 0.31078036]
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[[ 0.05272599 -0.13706132  0.03504692 ..., -0.13141023  0.1531008
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   0.20415199]]
Progress: 5.2% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.31944905]
 [-0.28837268]
 [-0.80043106]
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 [ 1.14849688]
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[[ 0.05324652 -0.13754879  0.03360607 ..., -0.13152903  0.15450037
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 [ 0.06253835 -0.03647172 -0.07900809 ...,  0.03854267  0.23280395
   0.20425296]]
Progress: 5.2% ... Training loss: 0.300 ... Validation loss: 0.457[[ 0.31713559]
 [-0.29068579]
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[[ 0.05332878 -0.13761685  0.03357248 ..., -0.1315435   0.15448494
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  -0.23388086]
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   0.20457559]]
Progress: 5.2% ... Training loss: 0.299 ... Validation loss: 0.450[[ 0.30729062]
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[[ 0.05219133 -0.13653392  0.03657391 ..., -0.1312953   0.15159095
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 [ 0.06218494 -0.03612019 -0.07811897 ...,  0.0386204   0.23215722
   0.20517227]]
Progress: 5.2% ... Training loss: 0.306 ... Validation loss: 0.461[[ 0.31719419]
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[[ 0.0525939  -0.13686051  0.03568665 ..., -0.13137235  0.15271321
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  -0.23473442]
 [ 0.06234836 -0.03627115 -0.0785324  ...,  0.03858774  0.23275162
   0.20479455]]
Progress: 5.2% ... Training loss: 0.301 ... Validation loss: 0.452[[ 0.31360175]
 [-0.29162485]
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[[ 0.05259726 -0.13685477  0.03569255 ..., -0.13136429  0.15286238
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   0.20547249]]
Progress: 5.2% ... Training loss: 0.298 ... Validation loss: 0.451[[ 0.32204237]
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[[ 0.05342044 -0.13769723  0.03352355 ..., -0.13156567  0.15513497
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   0.20569785]]
Progress: 5.2% ... Training loss: 0.308 ... Validation loss: 0.460[[ 0.30454768]
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[[ 0.05167614 -0.13609533  0.03793341 ..., -0.13121179  0.15089633
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  -0.232944  ]
 [ 0.06203232 -0.03594841 -0.0776269  ...,  0.0386614   0.23238292
   0.20561949]]
Progress: 5.2% ... Training loss: 0.312 ... Validation loss: 0.468[[ 0.32110928]
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[[ 0.0529271  -0.13731914  0.03463949 ..., -0.13152929  0.153998
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 [ 0.06235175 -0.03627832 -0.07850044 ...,  0.03857722  0.23329774
   0.20470282]]
Progress: 5.2% ... Training loss: 0.308 ... Validation loss: 0.462[[ 0.30936953]
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[[ 0.05195847 -0.13643086  0.037118   ..., -0.13134204  0.15159699
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 [ 0.0370164   0.05036889  0.12460738 ..., -0.2433019  -0.0514158
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   0.20414227]]
Progress: 5.2% ... Training loss: 0.300 ... Validation loss: 0.457[[ 0.31937656]
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[[ 0.05266439 -0.13713107  0.03520383 ..., -0.13150949  0.15357844
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 [-0.19177851 -0.18159613 -0.11796013 ...,  0.10824312 -0.0505289
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 [ 0.06260732 -0.0365192  -0.07913068 ...,  0.03852784  0.23423091
   0.20405501]]
Progress: 5.2% ... Training loss: 0.302 ... Validation loss: 0.460[[ 0.31133425]
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[[ 0.05215161 -0.13670447  0.03649527 ..., -0.13142079  0.15234651
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 ..., 
 [-0.19208813 -0.18132018 -0.11716636 ...,  0.10829994 -0.05119043
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  -0.23349658]
 [ 0.06256217 -0.03648874 -0.07900682 ...,  0.03853664  0.23418926
   0.20414935]]
Progress: 5.3% ... Training loss: 0.298 ... Validation loss: 0.454[[ 0.31468141]
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[[ 0.05159522 -0.13619943  0.03788767 ..., -0.13129834  0.15074559
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 [-0.19155254 -0.18181455 -0.11848252 ...,  0.10817748 -0.04988631
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   0.20307442]]
Progress: 5.3% ... Training loss: 0.296 ... Validation loss: 0.457[[ 0.3036588 ]
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[[ 0.05079346 -0.13544798  0.04001901 ..., -0.13110491  0.14832137
  -0.16696188]
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   0.20388422]]
Progress: 5.3% ... Training loss: 0.319 ... Validation loss: 0.478[[ 0.3265976 ]
 [-0.27804988]
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 [ 0.43521039]
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[[ 0.0525742  -0.13724437  0.03549661 ..., -0.1315808   0.15294637
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  -0.23366209]
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   0.20344355]]
Progress: 5.3% ... Training loss: 0.321 ... Validation loss: 0.492[[ 0.30899999]
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 [ 1.14246831]
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[[ 0.05177069 -0.13654565  0.03750034 ..., -0.13143695  0.15110767
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  -0.23206431]
 [ 0.06240855 -0.03638492 -0.07865125 ...,  0.03854869  0.23415026
   0.20446265]]
Progress: 5.3% ... Training loss: 0.301 ... Validation loss: 0.460[[ 0.3126489 ]
 [-0.29038439]
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[[ 0.05223685 -0.13697132  0.03632858 ..., -0.13155268  0.15219512
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  -0.23320612]
 [ 0.0627267  -0.03669443 -0.07951424 ...,  0.0384639   0.23497372
   0.20362775]]
Progress: 5.3% ... Training loss: 0.296 ... Validation loss: 0.459[[ 0.31389297]
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[[ 0.05213982 -0.13687075  0.03682007 ..., -0.13152933  0.15188041
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  -0.23451498]
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   0.20425594]]
Progress: 5.3% ... Training loss: 0.296 ... Validation loss: 0.460[[ 0.31917626]
 [-0.28423788]
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[[ 0.05188103 -0.13661533  0.03752278 ..., -0.13147053  0.15139185
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  -0.23476458]
 [ 0.06244971 -0.03640474 -0.07879575 ...,  0.03853329  0.23445359
   0.20438073]]
Progress: 5.3% ... Training loss: 0.299 ... Validation loss: 0.464[[ 0.32608606]
 [-0.27943914]
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[[ 0.05276872 -0.13740196  0.0353905  ..., -0.13166462  0.15347208
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   0.20325134]]
Progress: 5.3% ... Training loss: 0.317 ... Validation loss: 0.479[[ 0.30755577]
 [-0.29626015]
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[[ 0.05192189 -0.13668172  0.03736659 ..., -0.13149666  0.15143313
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  -0.23366655]
 [ 0.06239497 -0.03633604 -0.07862749 ...,  0.03854683  0.23450697
   0.20440442]]
Progress: 5.3% ... Training loss: 0.308 ... Validation loss: 0.466[[ 0.31533691]
 [-0.28975213]
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[[ 0.05180911 -0.13660547  0.03774308 ..., -0.13147613  0.1511955
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  -0.23419131]
 [ 0.06274353 -0.0366871  -0.07957231 ...,  0.03845266  0.23545693
   0.20349312]]
Progress: 5.3% ... Training loss: 0.295 ... Validation loss: 0.456[[ 0.31682451]
 [-0.28801739]
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[[ 0.05191896 -0.13667797  0.03757338 ..., -0.13148673  0.1513568  -0.169575  ]
 [ 0.03719145  0.0501611   0.12402021 ..., -0.24335834 -0.05088455
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 [ 0.06359422 -0.03745765 -0.08168341 ...,  0.03826329  0.23761083
   0.20145094]]
Progress: 5.3% ... Training loss: 0.296 ... Validation loss: 0.461[[ 0.3195798 ]
 [-0.28666481]
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[[ 0.05281041 -0.13753653  0.03530733 ..., -0.13169703  0.15376481
  -0.1717916 ]
 [ 0.03702612  0.05031558  0.12442691 ..., -0.2433218  -0.05131427
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 [-0.19216084 -0.18137749 -0.11704396 ...,  0.10825806 -0.05172537
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  -0.23443301]
 [ 0.06291203 -0.03679607 -0.07993929 ...,  0.03843185  0.23608918
   0.20316643]]
Progress: 5.3% ... Training loss: 0.297 ... Validation loss: 0.460[[ 0.31549597]
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[[ 0.05244836 -0.13719753  0.03617676 ..., -0.13161805  0.15297305
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 [ 0.06283802 -0.03671059 -0.07987416 ...,  0.03844618  0.23605618
   0.20336028]]
Progress: 5.3% ... Training loss: 0.295 ... Validation loss: 0.457[[ 0.31975493]
 [-0.28712544]
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[[ 0.05296564 -0.13768472  0.03496241 ..., -0.13174649  0.15427205
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 ..., 
 [-0.19181017 -0.18169933 -0.11783864 ...,  0.10818166 -0.05088903
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  -0.23471884]
 [ 0.06298651 -0.03684526 -0.08023653 ...,  0.03840926  0.23649042
   0.20299686]]
Progress: 5.3% ... Training loss: 0.297 ... Validation loss: 0.462[[ 0.32554641]
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[[ 0.05334191 -0.13800283  0.03415466 ..., -0.13183814  0.155022
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 [-0.1916718  -0.18181268 -0.11812279 ...,  0.10814725 -0.05061471
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 [ 0.06309749 -0.03696194 -0.08056345 ...,  0.0383796   0.23680768
   0.20270349]]
Progress: 5.4% ... Training loss: 0.307 ... Validation loss: 0.479[[ 0.31447353]
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[[ 0.05236878 -0.13713833  0.03679257 ..., -0.13163324  0.15252846
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   0.20336823]]
Progress: 5.4% ... Training loss: 0.298 ... Validation loss: 0.458[[ 0.31145254]
 [-0.29373972]
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[[ 0.05205781 -0.13684199  0.03757271 ..., -0.13154683  0.1516825
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   0.20309648]]
Progress: 5.4% ... Training loss: 0.302 ... Validation loss: 0.464[[ 0.33259408]
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[[ 0.05288622 -0.1376318   0.03555956 ..., -0.13176768  0.15372771
  -0.1718257 ]
 [ 0.0373974   0.04997197  0.1234658  ..., -0.24341185 -0.05036297
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 [ 0.063387   -0.03724124 -0.08130788 ...,  0.03829341  0.23787307
   0.20193395]]
Progress: 5.4% ... Training loss: 0.338 ... Validation loss: 0.507[[ 0.310833  ]
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[[ 0.051062   -0.1360878   0.03996797 ..., -0.13143364  0.14946271
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  -0.23380402]
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   0.20334377]]
Progress: 5.4% ... Training loss: 0.303 ... Validation loss: 0.466[[ 0.30657416]
 [-0.29772924]
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   0.20438268]]
Progress: 5.4% ... Training loss: 0.316 ... Validation loss: 0.479[[ 0.32578348]
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[[ 0.05257671 -0.13753752  0.0362781  ..., -0.1318552   0.15311441
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   0.20319512]]
Progress: 5.4% ... Training loss: 0.309 ... Validation loss: 0.480[[ 0.31662293]
 [-0.28953835]
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[[ 0.0520134  -0.13707208  0.03765111 ..., -0.13173417  0.15175905
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   0.20380417]]
Progress: 5.4% ... Training loss: 0.296 ... Validation loss: 0.463[[ 0.31595467]
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   0.20391253]]
Progress: 5.4% ... Training loss: 0.295 ... Validation loss: 0.460[[ 0.31550046]
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[[ 0.0518742  -0.1369363   0.03819955 ..., -0.13168448  0.15135647
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   0.20419119]]
Progress: 5.4% ... Training loss: 0.295 ... Validation loss: 0.459[[ 0.31105687]
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[[ 0.05141181 -0.13651132  0.03937284 ..., -0.13157987  0.15020529
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   0.20585947]]
Progress: 5.4% ... Training loss: 0.301 ... Validation loss: 0.463[[ 0.316689  ]
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[[ 0.05159916 -0.13672157  0.03891604 ..., -0.13164109  0.15057612
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   0.20580401]]
Progress: 5.4% ... Training loss: 0.295 ... Validation loss: 0.459[[ 0.32168443]
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[[ 0.05239713 -0.13744338  0.03708993 ..., -0.13181527  0.15228882
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 [-0.19104341 -0.18249685 -0.119835   ...,  0.10792065 -0.04951183
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 [ 0.06162553 -0.03561443 -0.07695274 ...,  0.03869162  0.23454306
   0.20624894]]
Progress: 5.4% ... Training loss: 0.300 ... Validation loss: 0.463[[ 0.30192238]
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[[ 0.05087556 -0.13607321  0.04090081 ..., -0.13146033  0.14849741
  -0.1667829 ]
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   0.2053513 ]]
Progress: 5.4% ... Training loss: 0.333 ... Validation loss: 0.501[[ 0.32218807]
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[[ 0.05157999 -0.13680673  0.0390675  ..., -0.13167637  0.15033329
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 [-0.19112899 -0.18247301 -0.11974028 ...,  0.10790793 -0.04975382
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   0.2044108 ]]
Progress: 5.4% ... Training loss: 0.300 ... Validation loss: 0.462[[ 0.30702092]
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[[ 0.05056685 -0.13590239  0.04156425 ..., -0.13145905  0.14779563
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   0.20434077]]
Progress: 5.5% ... Training loss: 0.317 ... Validation loss: 0.482[[ 0.33114609]
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[[ 0.05240737 -0.137718    0.03671139 ..., -0.13197461  0.15246678
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   0.2025539 ]]
Progress: 5.5% ... Training loss: 0.328 ... Validation loss: 0.485[[ 0.31721752]
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 [ 0.42567567]
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[[ 0.05159646 -0.13698866  0.03886536 ..., -0.13181958  0.15036673
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   0.202821  ]]
Progress: 5.5% ... Training loss: 0.295 ... Validation loss: 0.455[[ 0.31412   ]
 [-0.29404396]
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[[ 0.05141087 -0.13681292  0.03937643 ..., -0.13178227  0.14993264
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   0.20351396]]
Progress: 5.5% ... Training loss: 0.298 ... Validation loss: 0.461[[ 0.31880748]
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[[ 0.05198702 -0.13733956  0.0381359  ..., -0.13193785  0.15119118
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   0.20187733]]
Progress: 5.5% ... Training loss: 0.295 ... Validation loss: 0.460[[ 0.31473267]
 [-0.29286123]
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[[ 0.05113174 -0.13656707  0.04022291 ..., -0.13173632  0.14900874
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   0.20131204]]
Progress: 5.5% ... Training loss: 0.297 ... Validation loss: 0.462[[ 0.32812725]
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[[ 0.05260315 -0.13792462  0.03670363 ..., -0.13210156  0.15246666
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   0.2014229 ]]
Progress: 5.5% ... Training loss: 0.318 ... Validation loss: 0.470[[ 0.31483193]
 [-0.29183847]
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[[ 0.05260388 -0.13792678  0.03680837 ..., -0.13210043  0.15228149
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   0.20118559]]
Progress: 5.5% ... Training loss: 0.297 ... Validation loss: 0.455[[ 0.32170253]
 [-0.28457445]
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[[ 0.05331831 -0.13860994  0.0349659  ..., -0.1322948   0.1542627
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   0.20155723]]
Progress: 5.5% ... Training loss: 0.298 ... Validation loss: 0.456[[ 0.32240207]
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[[ 0.05421725 -0.13943596  0.03260948 ..., -0.13249737  0.15630212
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 [ 0.06306316 -0.03695855 -0.08057048 ...,  0.03832941  0.2394799
   0.20261683]]
Progress: 5.5% ... Training loss: 0.299 ... Validation loss: 0.462[[ 0.31625369]
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[[ 0.05356079 -0.13885255  0.03427415 ..., -0.13236117  0.15492427
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   0.20273363]]
Progress: 5.5% ... Training loss: 0.296 ... Validation loss: 0.455[[ 0.31890785]
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[[ 0.05385299 -0.1391178   0.03352414 ..., -0.13243573  0.15554919
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   0.20407595]]
Progress: 5.5% ... Training loss: 0.295 ... Validation loss: 0.456[[ 0.32463131]
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[[ 0.05424086 -0.13948774  0.03249272 ..., -0.13253132  0.15656643
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 [-0.19009716 -0.1835044  -0.12237042 ...,  0.10760817 -0.04775748
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 [ 0.06262208 -0.03651254 -0.07943864 ...,  0.03844712  0.2386597
   0.20371499]]
Progress: 5.5% ... Training loss: 0.302 ... Validation loss: 0.463[[ 0.3263844 ]
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[[ 0.05493082 -0.14012062  0.03091922 ..., -0.13267943  0.15837752
  -0.17712471]
 [ 0.03695997  0.05034103  0.12428248 ..., -0.24334192 -0.05113985
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 [ 0.06276844 -0.0366266  -0.07980109 ...,  0.03841718  0.23916614
   0.20337125]]
Progress: 5.5% ... Training loss: 0.305 ... Validation loss: 0.465[[ 0.31157466]
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[[ 0.05307544 -0.13850774  0.03536519 ..., -0.13226641  0.15372601
  -0.17258032]
 [ 0.03699931  0.0503095   0.124191   ..., -0.24334925 -0.05107199
   0.12911502]
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 [-0.19097019 -0.18274673 -0.12030803 ...,  0.10779253 -0.04992486
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  -0.23419415]
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   0.20487775]]
Progress: 5.5% ... Training loss: 0.306 ... Validation loss: 0.467[[ 0.32722151]
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[[ 0.05463331 -0.14004398  0.03131225 ..., -0.13269673  0.15759457
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 [ 0.06227846 -0.03621834 -0.07866082 ...,  0.03852112  0.23811414
   0.20456289]]
Progress: 5.6% ... Training loss: 0.305 ... Validation loss: 0.470[[ 0.32269901]
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   0.20491899]]
Progress: 5.6% ... Training loss: 0.296 ... Validation loss: 0.456[[ 0.31997677]
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[[ 0.05422263 -0.1396532   0.03255739 ..., -0.13259846  0.15644032
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 [ 0.06216243 -0.03609027 -0.07838213 ...,  0.03855487  0.23802347
   0.20491533]]
Progress: 5.6% ... Training loss: 0.295 ... Validation loss: 0.457[[ 0.32328005]
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[[ 0.05426543 -0.13969785  0.03262699 ..., -0.1326146   0.15635633
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  -0.23478809]
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   0.20473712]]
Progress: 5.6% ... Training loss: 0.297 ... Validation loss: 0.461[[ 0.32388585]
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  -0.23469775]
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   0.20495167]]
Progress: 5.6% ... Training loss: 0.297 ... Validation loss: 0.462[[ 0.32434411]
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[[ 0.05418636 -0.13964854  0.03299293 ..., -0.13259776  0.15617817
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  -0.23381153]
 [ 0.061987   -0.0359035  -0.07794456 ...,  0.03859523  0.2378053
   0.20524273]]
Progress: 5.6% ... Training loss: 0.297 ... Validation loss: 0.466[[ 0.32331732]
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   0.20537942]]
Progress: 5.6% ... Training loss: 0.295 ... Validation loss: 0.463[[ 0.3210974 ]
 [-0.28891555]
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[[ 0.05328771 -0.13883533  0.03524281 ..., -0.13238793  0.15379123
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   0.20547875]]
Progress: 5.6% ... Training loss: 0.295 ... Validation loss: 0.462[[ 0.32669192]
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[[ 0.05373292 -0.13918867  0.03420057 ..., -0.13246923  0.15471302
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 [ 0.06188561 -0.03578988 -0.07764343 ...,  0.03863574  0.23775312
   0.20541304]]
Progress: 5.6% ... Training loss: 0.302 ... Validation loss: 0.468[[ 0.31563906]
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[[ 0.05314355 -0.13867783  0.03564203 ..., -0.13235303  0.15322295
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 [ 0.06154058 -0.03548966 -0.0767804  ...,  0.03871109  0.23703552
   0.20623452]]
Progress: 5.6% ... Training loss: 0.298 ... Validation loss: 0.462[[ 0.32796399]
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[[ 0.05423794 -0.13969327  0.03298314 ..., -0.13265117  0.15590994
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   0.20546035]]
Progress: 5.6% ... Training loss: 0.306 ... Validation loss: 0.475[[ 0.31303563]
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[[ 0.05293667 -0.1385451   0.0361788  ..., -0.13236578  0.15249051
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 [ 0.06175241 -0.03569562 -0.07738034 ...,  0.03865218  0.23764816
   0.20561675]]
Progress: 5.6% ... Training loss: 0.304 ... Validation loss: 0.465[[ 0.32921051]
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[[ 0.05377894 -0.13932235  0.03423692 ..., -0.13258169  0.15441632
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   0.20595999]]
Progress: 5.6% ... Training loss: 0.311 ... Validation loss: 0.485[[ 0.31123113]
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[[ 0.05265403 -0.1383059   0.03708251 ..., -0.13233503  0.15145465
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 [ 0.06101551 -0.03502403 -0.07555593 ...,  0.03882339  0.23611442
   0.20740949]]
Progress: 5.6% ... Training loss: 0.309 ... Validation loss: 0.466[[ 0.32400011]
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[[ 0.05332985 -0.13895278  0.03535084 ..., -0.13252401  0.15343797
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 [ 0.06184004 -0.03579704 -0.07771147 ...,  0.03859652  0.23844706
   0.20531041]]
Progress: 5.6% ... Training loss: 0.297 ... Validation loss: 0.465[[ 0.31051879]
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[[ 0.05194609 -0.13773789  0.03869115 ..., -0.13221148  0.1499007
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 [-0.19173135 -0.18216891 -0.11842792 ...,  0.10789856 -0.05260059
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   0.20610904]]
Progress: 5.7% ... Training loss: 0.313 ... Validation loss: 0.471[[ 0.31415084]
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[[ 0.05168387 -0.13744395  0.03947074 ..., -0.13213846  0.14936205
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   0.2053837 ]]
Progress: 5.7% ... Training loss: 0.301 ... Validation loss: 0.461[[ 0.32404338]
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[[ 0.05204366 -0.13777186  0.03862511 ..., -0.13223313  0.15035601
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   0.20459265]]
Progress: 5.7% ... Training loss: 0.300 ... Validation loss: 0.473[[ 0.32011586]
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[[ 0.05217262 -0.13790831  0.03831824 ..., -0.13226656  0.15073158
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   0.20345093]]
Progress: 5.7% ... Training loss: 0.295 ... Validation loss: 0.459[[ 0.30671263]
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[[ 0.05181683 -0.13755912  0.03929376 ..., -0.13217755  0.1499372
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   0.20577385]]
Progress: 5.7% ... Training loss: 0.322 ... Validation loss: 0.477[[ 0.32537828]
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[[ 0.05242995 -0.13819968  0.03763271 ..., -0.13236031  0.15143363
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 [ 0.06221898 -0.036145   -0.0785963  ...,  0.03847509  0.23999946
   0.20418661]]
Progress: 5.7% ... Training loss: 0.299 ... Validation loss: 0.471[[ 0.31995685]
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[[ 0.05192155 -0.13771411  0.03910647 ..., -0.13222615  0.14999377
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   0.20514399]]
Progress: 5.7% ... Training loss: 0.295 ... Validation loss: 0.461[[ 0.32493573]
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[[ 0.05215727 -0.13794008  0.03847394 ..., -0.13228253  0.15043483
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   0.20605631]]
Progress: 5.7% ... Training loss: 0.298 ... Validation loss: 0.471[[ 0.31777164]
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[[ 0.05172415 -0.13754273  0.0395528  ..., -0.13218268  0.14940069
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 [ 0.06145131 -0.03544492 -0.07665394 ...,  0.03866545  0.23834234
   0.20606522]]
Progress: 5.7% ... Training loss: 0.296 ... Validation loss: 0.462[[ 0.3230807 ]
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[[ 0.0522714  -0.13803371  0.03826686 ..., -0.13232261  0.15083387
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   0.20473187]]
Progress: 5.7% ... Training loss: 0.297 ... Validation loss: 0.466[[ 0.3192761 ]
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[[ 0.05251647 -0.13825458  0.03757277 ..., -0.13240204  0.1515024
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   0.20520446]]
Progress: 5.7% ... Training loss: 0.294 ... Validation loss: 0.456[[ 0.31647988]
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[[ 0.05220104 -0.13797294  0.03842318 ..., -0.13232842  0.15086429
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   0.20618709]]
Progress: 5.7% ... Training loss: 0.297 ... Validation loss: 0.458[[ 0.3200498 ]
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[[ 0.05249697 -0.13826791  0.03764498 ..., -0.13240807  0.1516139
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 [ 0.06148181 -0.03543838 -0.0767075  ...,  0.03865476  0.238982    0.2058773 ]]
Progress: 5.7% ... Training loss: 0.294 ... Validation loss: 0.461[[ 0.31214477]
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[[ 0.05209754 -0.13793119  0.0387799  ..., -0.13230133  0.15055052
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 [-0.19182557 -0.1821508  -0.11816278 ...,  0.10790716 -0.05314003
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   0.2071238 ]]
Progress: 5.7% ... Training loss: 0.304 ... Validation loss: 0.466[[ 0.3272567 ]
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[[ 0.05318091 -0.13897092  0.03607778 ..., -0.13258549  0.15316025
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   0.2063985 ]]
Progress: 5.7% ... Training loss: 0.309 ... Validation loss: 0.484[[ 0.30897675]
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[[ 0.05186787 -0.1378032   0.03950518 ..., -0.13228656  0.14988731
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   0.20790757]]
Progress: 5.8% ... Training loss: 0.312 ... Validation loss: 0.469[[ 0.32279061]
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 [ 1.17052591]
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[[ 0.05276385 -0.1386973   0.03719807 ..., -0.13254484  0.15233725
  -0.1713941 ]
 [ 0.03746042  0.04988614  0.12278917 ..., -0.24346898 -0.04965438
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   0.20667307]]
Progress: 5.8% ... Training loss: 0.298 ... Validation loss: 0.459[[ 0.32463168]
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   0.20642863]]
Progress: 5.8% ... Training loss: 0.302 ... Validation loss: 0.458[[ 0.30861317]
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[[ 0.05249287 -0.13842375  0.03827405 ..., -0.13249348  0.15129294
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  -0.2333955 ]
 [ 0.06033933 -0.03444867 -0.07393484 ...,  0.03889237  0.23675875
   0.2084923 ]]
Progress: 5.8% ... Training loss: 0.310 ... Validation loss: 0.464[[ 0.32297889]
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[[ 0.05339028 -0.13930901  0.03601823 ..., -0.13273962  0.15362825
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   0.20890856]]
Progress: 5.8% ... Training loss: 0.298 ... Validation loss: 0.462[[ 0.3146125 ]
 [-0.29023282]
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[[ 0.05282291 -0.13883407  0.03749924 ..., -0.13261805  0.15216164
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   0.21052644]]
Progress: 5.8% ... Training loss: 0.296 ... Validation loss: 0.454[[ 0.3219663 ]
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[[ 0.05363284 -0.13958365  0.03540061 ..., -0.13282779  0.15446552
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 [ 0.06057244 -0.03471982 -0.07469118 ...,  0.03882073  0.23783896
   0.20789817]]
Progress: 5.8% ... Training loss: 0.298 ... Validation loss: 0.456[[ 0.30190426]
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[[ 0.05204368 -0.13813311  0.03945733 ..., -0.13244334  0.15043903
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   0.20919051]]
Progress: 5.8% ... Training loss: 0.336 ... Validation loss: 0.489[[ 0.32356048]
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[[ 0.05337198 -0.13946794  0.03593332 ..., -0.13284105  0.15390934
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   0.20775521]]
Progress: 5.8% ... Training loss: 0.302 ... Validation loss: 0.467[[ 0.30038223]
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[[ 0.05172084 -0.13800978  0.03995897 ..., -0.13247716  0.14991076
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 [ 0.05968841 -0.03398652 -0.07268035 ...,  0.03897708  0.23611305
   0.20984336]]
Progress: 5.8% ... Training loss: 0.344 ... Validation loss: 0.502[[ 0.31828943]
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[[ 0.05252607 -0.13882318  0.03786954 ..., -0.13272814  0.15207214
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 [-0.19181173 -0.18227964 -0.1183652  ...,  0.10779657 -0.05340288
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   0.20867198]]
Progress: 5.8% ... Training loss: 0.296 ... Validation loss: 0.463[[ 0.31979122]
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[[ 0.05346364 -0.13972775  0.03557115 ..., -0.13295995  0.15453371
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   0.20760396]]
Progress: 5.8% ... Training loss: 0.296 ... Validation loss: 0.461[[ 0.31499226]
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[[ 0.05329895 -0.13959017  0.03594806 ..., -0.13292474  0.15395424
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   0.20832862]]
Progress: 5.8% ... Training loss: 0.295 ... Validation loss: 0.458[[ 0.31597864]
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[[ 0.05320507 -0.13947644  0.03631713 ..., -0.13287969  0.1536679
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 [-0.19108026 -0.18294883 -0.12015175 ...,  0.10761178 -0.05165781
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   0.20967594]]
Progress: 5.8% ... Training loss: 0.294 ... Validation loss: 0.457[[ 0.32081178]
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[[ 0.0541622  -0.14039192  0.03388824 ..., -0.13311959  0.15593875
  -0.1756748 ]
 [ 0.03720472  0.05011551  0.1233741  ..., -0.24341428 -0.05025764
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   0.20968814]]
Progress: 5.8% ... Training loss: 0.298 ... Validation loss: 0.458[[ 0.32780639]
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   0.20891294]]
Progress: 5.9% ... Training loss: 0.314 ... Validation loss: 0.477[[ 0.31985032]
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   0.20803198]]
Progress: 5.9% ... Training loss: 0.296 ... Validation loss: 0.452[[ 0.30744364]
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[[ 0.05389646 -0.14012177  0.03479453 ..., -0.13303667  0.15532279
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   0.20805577]]
Progress: 5.9% ... Training loss: 0.309 ... Validation loss: 0.460[[ 0.33462548]
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[[ 0.05549107 -0.14172831  0.03063776 ..., -0.13348838  0.15942026
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   0.20700213]]
Progress: 5.9% ... Training loss: 0.353 ... Validation loss: 0.518[[ 0.30907169]
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 [ 0.06046929 -0.03473528 -0.0749577  ...,  0.03876411  0.23886529
   0.20777443]]
Progress: 5.9% ... Training loss: 0.307 ... Validation loss: 0.459[[ 0.33344317]
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[[ 0.05505836 -0.14163702  0.03150859 ..., -0.13356624  0.15869393
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   0.20741992]]
Progress: 5.9% ... Training loss: 0.341 ... Validation loss: 0.500[[ 0.30784418]
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   0.21161965]]
Progress: 5.9% ... Training loss: 0.311 ... Validation loss: 0.461[[ 0.32641091]
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 [ 0.05921483 -0.03368977 -0.07196048 ...,  0.03897418  0.2365164
   0.21067507]]
Progress: 5.9% ... Training loss: 0.312 ... Validation loss: 0.465[[ 0.30641979]
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   0.21229157]]
Progress: 5.9% ... Training loss: 0.313 ... Validation loss: 0.468[[ 0.31941872]
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[[ 0.05458405 -0.14157579  0.0323114  ..., -0.13369822  0.15788038
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   0.21253236]]
Progress: 5.9% ... Training loss: 0.296 ... Validation loss: 0.456[[ 0.31072223]
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[[ 0.05402523 -0.14104096  0.03377839 ..., -0.13355714  0.15651225
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   0.21337131]]
Progress: 5.9% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.31721581]
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[[ 0.05371274 -0.14073562  0.03449176 ..., -0.13347382  0.15572431
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   0.2123191 ]]
Progress: 5.9% ... Training loss: 0.294 ... Validation loss: 0.452[[ 0.3134639 ]
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[[ 0.05279924 -0.13990128  0.03688634 ..., -0.13324549  0.15330906
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   0.2119812 ]]
Progress: 5.9% ... Training loss: 0.297 ... Validation loss: 0.456[[ 0.31302783]
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[[ 0.05187454 -0.13900449  0.03933437 ..., -0.13299843  0.15086694
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   0.21189882]]
Progress: 5.9% ... Training loss: 0.298 ... Validation loss: 0.460[[ 0.3177866 ]
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[[ 0.05206231 -0.13919486  0.03892697 ..., -0.13304982  0.15123364
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   0.21105107]]
Progress: 5.9% ... Training loss: 0.295 ... Validation loss: 0.459[[ 0.32720662]
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[[ 0.052775   -0.13989925  0.03715139 ..., -0.13323855  0.15322095
  -0.17454538]
 [ 0.03686668  0.05044116  0.12418134 ..., -0.24333388 -0.05111445
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  -0.23350944]
 [ 0.05940271 -0.033839   -0.07237383 ...,  0.03891112  0.23793253
   0.21029009]]
Progress: 6.0% ... Training loss: 0.306 ... Validation loss: 0.470[[ 0.3128348 ]
 [-0.29299846]
 [-0.80624093]
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 [ 0.41891433]
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[[ 0.05157871 -0.13882627  0.04022119 ..., -0.13298032  0.15008255
  -0.17175199]
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  -0.23261914]
 [ 0.05890212 -0.03339382 -0.07117484 ...,  0.03902417  0.23676557
   0.21149332]]
Progress: 6.0% ... Training loss: 0.299 ... Validation loss: 0.461[[ 0.31377631]
 [-0.29121875]
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 [ 1.17055511]
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[[ 0.05146847 -0.13868551  0.04060304 ..., -0.13293734  0.14982774
  -0.17130464]
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  -0.23366525]
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   0.21130636]]
Progress: 6.0% ... Training loss: 0.295 ... Validation loss: 0.457[[ 0.31617006]
 [-0.28926236]
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[[ 0.05157946 -0.13880151  0.04035997 ..., -0.13296753  0.15003535
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  -0.23370649]
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   0.21081344]]
Progress: 6.0% ... Training loss: 0.294 ... Validation loss: 0.458[[ 0.31494546]
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[[ 0.05185926 -0.13902301  0.03970277 ..., -0.13300898  0.15066206
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  -0.23374736]
 [ 0.05914141 -0.03359831 -0.0717805  ...,  0.03897101  0.23765096
   0.21094052]]
Progress: 6.0% ... Training loss: 0.294 ... Validation loss: 0.456[[ 0.32449918]
 [-0.28364368]
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[[ 0.05211336 -0.13930418  0.03909263 ..., -0.13307689  0.15140264
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  -0.23396951]
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   0.21032741]]
Progress: 6.0% ... Training loss: 0.299 ... Validation loss: 0.463[[ 0.31798498]
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[[ 0.0522973  -0.13950166  0.0387039  ..., -0.13312691  0.15191085
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 [-0.19110343 -0.1832003  -0.1201798  ...,  0.10746508 -0.05238682
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  -0.23392695]
 [ 0.05969826 -0.03411213 -0.07320519 ...,  0.0388431   0.2393738
   0.20953557]]
Progress: 6.0% ... Training loss: 0.293 ... Validation loss: 0.455[[ 0.32038594]
 [-0.28867821]
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[[ 0.0524011  -0.13958172  0.03855491 ..., -0.13316024  0.15223509
  -0.1736712 ]
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  -0.23373398]
 [ 0.05978959 -0.03420128 -0.07347298 ...,  0.03881907  0.23979434
   0.20928352]]
Progress: 6.0% ... Training loss: 0.293 ... Validation loss: 0.455[[ 0.31574613]
 [-0.29255126]
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[[ 0.05215895 -0.13938158  0.03916705 ..., -0.13310872  0.15164585
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  -0.23316057]
 [ 0.06030531 -0.03465872 -0.07473019 ...,  0.03869969  0.24121241
   0.20803819]]
Progress: 6.0% ... Training loss: 0.296 ... Validation loss: 0.457[[ 0.31787503]
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[[ 0.05206208 -0.13928531  0.03944686 ..., -0.13307725  0.15138274
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 [ 0.06032293 -0.03467784 -0.07482855 ...,  0.0386935   0.24133444
   0.20800597]]
Progress: 6.0% ... Training loss: 0.294 ... Validation loss: 0.459[[ 0.31407616]
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[[ 0.05163367 -0.13887146  0.04069759 ..., -0.13295939  0.15017148
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  -0.23379504]
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   0.20910878]]
Progress: 6.0% ... Training loss: 0.298 ... Validation loss: 0.463[[ 0.31347274]
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[[ 0.05162497 -0.13888433  0.04079386 ..., -0.13296592  0.15026181
  -0.17167335]
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 [-0.19108304 -0.18321194 -0.12012253 ...,  0.10745235 -0.05242872
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   0.20934533]]
Progress: 6.0% ... Training loss: 0.300 ... Validation loss: 0.465[[ 0.32605237]
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[[ 0.05254514 -0.13976314  0.03850439 ..., -0.1332192   0.15253464
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 [-0.1910283  -0.18326512 -0.12028951 ...,  0.10743604 -0.05232792
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  -0.23396172]
 [ 0.06016193 -0.03450258 -0.07439823 ...,  0.03873636  0.24116675
   0.20851365]]
Progress: 6.0% ... Training loss: 0.305 ... Validation loss: 0.477[[ 0.31281315]
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[[ 0.05164218 -0.1389629   0.04086693 ..., -0.13300143  0.1500439
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   0.20880803]]
Progress: 6.0% ... Training loss: 0.302 ... Validation loss: 0.466[[ 0.32552474]
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[[ 0.05316044 -0.14040688  0.03702828 ..., -0.13342544  0.15381677
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   0.20881128]]
Progress: 6.0% ... Training loss: 0.301 ... Validation loss: 0.469[[ 0.32009485]
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 [ 1.18294701]
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[[ 0.05349535 -0.14065244  0.03629946 ..., -0.13350006  0.1544144
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   0.21004737]]
Progress: 6.1% ... Training loss: 0.294 ... Validation loss: 0.457[[ 0.31767996]
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[[ 0.05277564 -0.14000236  0.03821575 ..., -0.13332646  0.15249599
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   0.21013563]]
Progress: 6.1% ... Training loss: 0.295 ... Validation loss: 0.461[[ 0.32192927]
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[[ 0.05371245 -0.14085219  0.03601954 ..., -0.13357951  0.15477104
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 [ 0.05964409 -0.03400212 -0.07299149 ...,  0.03887115  0.24038848
   0.20973769]]
Progress: 6.1% ... Training loss: 0.297 ... Validation loss: 0.464[[ 0.31890491]
 [-0.28524775]
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 [ 1.18466891]
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[[ 0.05341686 -0.14055296  0.03698751 ..., -0.13350073  0.15385369
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  -0.23298325]
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   0.21042113]]
Progress: 6.1% ... Training loss: 0.294 ... Validation loss: 0.459[[ 0.32461198]
 [-0.28073726]
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[[ 0.05428437 -0.14136196  0.03486677 ..., -0.13373339  0.15616231
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   0.21031073]]
Progress: 6.1% ... Training loss: 0.302 ... Validation loss: 0.467[[ 0.31412022]
 [-0.28967976]
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[[ 0.05385779 -0.14096503  0.03595976 ..., -0.13363222  0.15527383
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 [ 0.05927034 -0.03363685 -0.07195295 ...,  0.03896448  0.23979976
   0.21060564]]
Progress: 6.1% ... Training loss: 0.295 ... Validation loss: 0.455[[ 0.32325372]
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[[ 0.05427387 -0.14133159  0.03499737 ..., -0.13374328  0.15629473
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   0.20893211]]
Progress: 6.1% ... Training loss: 0.299 ... Validation loss: 0.458[[ 0.3129423 ]
 [-0.29072807]
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[[ 0.05370747 -0.14080259  0.03651646 ..., -0.1336033   0.15482177
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   0.20973887]]
Progress: 6.1% ... Training loss: 0.297 ... Validation loss: 0.456[[ 0.31896944]
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[[ 0.05424691 -0.14128788  0.03506052 ..., -0.13375243  0.1562333
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 [-0.19087316 -0.18342924 -0.1205462  ...,  0.10733692 -0.0523554
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   0.21014996]]
Progress: 6.1% ... Training loss: 0.294 ... Validation loss: 0.452[[ 0.32065071]
 [-0.28374185]
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[[ 0.05483122 -0.14181448  0.03381108 ..., -0.13392133  0.1577759
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  -0.23295294]
 [ 0.05968699 -0.03399068 -0.0730965  ...,  0.03885109  0.24141995
   0.209628  ]]
Progress: 6.1% ... Training loss: 0.297 ... Validation loss: 0.449[[ 0.32250702]
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[[ 0.05494134 -0.14192612  0.03359748 ..., -0.13395915  0.1580605
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 [-0.19055894 -0.18371566 -0.1211576  ...,  0.10725484 -0.05162177
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  -0.23230926]
 [ 0.0596484  -0.03396023 -0.07300115 ...,  0.03886556  0.24137797
   0.2097042 ]]
Progress: 6.1% ... Training loss: 0.299 ... Validation loss: 0.450[[ 0.31827588]
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[[ 0.0543736  -0.14143175  0.03505149 ..., -0.1338247   0.15660626
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 [ 0.03792655  0.04946358  0.12134798 ..., -0.24361438 -0.04828054
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 [-0.19099256 -0.18334088 -0.12012288 ...,  0.10736353 -0.05275974
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  -0.23192338]
 [ 0.05994443 -0.03419933 -0.07363138 ...,  0.0387943   0.24212822
   0.20905426]]
Progress: 6.1% ... Training loss: 0.293 ... Validation loss: 0.451[[ 0.30325439]
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[[ 0.05331796 -0.14040614  0.0380006  ..., -0.13353289  0.15390164
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 [ 0.03792495  0.04946335  0.12135351 ..., -0.24361448 -0.04827965
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 [-0.19122051 -0.18312506 -0.11953057 ...,  0.10742225 -0.053372
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   0.21131099]]
Progress: 6.1% ... Training loss: 0.334 ... Validation loss: 0.494[[ 0.33835709]
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 [ 1.20329426]
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[[ 0.05630208 -0.14342591  0.03014545 ..., -0.13449675  0.16150653
  -0.18232659]
 [ 0.03797012  0.04941787  0.12119723 ..., -0.24362729 -0.04816415
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 [-0.1909856  -0.18335714 -0.12017059 ...,  0.10734803 -0.05274094
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   0.20852977]]
Progress: 6.1% ... Training loss: 0.365 ... Validation loss: 0.531[[ 0.30289906]
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[[ 0.05404289 -0.14156337  0.03558698 ..., -0.1340248   0.15576844
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   0.20988895]]
Progress: 6.1% ... Training loss: 0.333 ... Validation loss: 0.488[[ 0.32691278]
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[[ 0.05644149 -0.14396784  0.02929406 ..., -0.13483057  0.16190137
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   0.20854513]]
Progress: 6.2% ... Training loss: 0.313 ... Validation loss: 0.473[[ 0.31785826]
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[[ 0.05572968 -0.14337238  0.03103241 ..., -0.13466278  0.16020688
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   0.20864295]]
Progress: 6.2% ... Training loss: 0.293 ... Validation loss: 0.452[[ 0.32165318]
 [-0.28637471]
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[[ 0.05594966 -0.14352953  0.03072529 ..., -0.13470353  0.16061248
  -0.1822069 ]
 [ 0.03749358  0.0498258   0.12236002 ..., -0.24352571 -0.04939013
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   0.20911808]]
Progress: 6.2% ... Training loss: 0.296 ... Validation loss: 0.456[[ 0.32395923]
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[[ 0.05640701 -0.14396589  0.02973394 ..., -0.13482642  0.16179127
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 [ 0.05977184 -0.0342108  -0.07344309 ...,  0.03871545  0.24280755
   0.20903306]]
Progress: 6.2% ... Training loss: 0.299 ... Validation loss: 0.463[[ 0.30739635]
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[[ 0.05544556 -0.14306675  0.03227947 ..., -0.13457142  0.15945543
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   0.21038536]]
Progress: 6.2% ... Training loss: 0.307 ... Validation loss: 0.462[[ 0.32571925]
 [-0.28138773]
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[[ 0.05599235 -0.14361565  0.03088925 ..., -0.13472935  0.16086032
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 [ 0.05967672 -0.03412114 -0.07330117 ...,  0.03873601  0.24286816
   0.20918746]]
Progress: 6.2% ... Training loss: 0.307 ... Validation loss: 0.478[[ 0.31778709]
 [-0.28940582]
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[[ 0.05497094 -0.14272908  0.03341954 ..., -0.13448409  0.15818369
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   0.20982495]]
Progress: 6.2% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.3158873 ]
 [-0.29159849]
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[[ 0.05438845 -0.14221455  0.03491267 ..., -0.13433322  0.15683494
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   0.20987423]]
Progress: 6.2% ... Training loss: 0.294 ... Validation loss: 0.451[[ 0.31726422]
 [-0.29028256]
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[[ 0.05462486 -0.14240092  0.03443053 ..., -0.13439686  0.15736213
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 [-0.19145358 -0.18313554 -0.1191977  ...,  0.10729834 -0.05399578
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  -0.235165  ]
 [ 0.0595501  -0.03401813 -0.07288759 ...,  0.03876864  0.24276648
   0.20952659]]
Progress: 6.2% ... Training loss: 0.293 ... Validation loss: 0.450[[ 0.30461215]
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[[ 0.0533194  -0.14120698  0.03769992 ..., -0.13406043  0.15414172
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 [-0.1921181  -0.18254617 -0.11752    ...,  0.10746967 -0.05567789
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   0.2111383 ]]
Progress: 6.2% ... Training loss: 0.325 ... Validation loss: 0.474[[ 0.330099  ]
 [-0.27958027]
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[[ 0.0551241  -0.14304195  0.03302415 ..., -0.13461264  0.15887412
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 [-0.19166119 -0.18300192 -0.11863657 ...,  0.10732504 -0.054607
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   0.21023886]]
Progress: 6.2% ... Training loss: 0.317 ... Validation loss: 0.482[[ 0.31230004]
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[[ 0.05422792 -0.14225176  0.03528294 ..., -0.13439869  0.15651108
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   0.21030865]]
Progress: 6.2% ... Training loss: 0.301 ... Validation loss: 0.456[[ 0.32717995]
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[[ 0.05471269 -0.1427551   0.03400191 ..., -0.13455365  0.1577573
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 [ 0.06023522 -0.03470329 -0.07487828 ...,  0.03854133  0.24529705
   0.20773501]]
Progress: 6.2% ... Training loss: 0.300 ... Validation loss: 0.464[[ 0.316309  ]
 [-0.29266209]
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[[ 0.05347218 -0.14170031  0.03697894 ..., -0.13427059  0.15469053
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 [ 0.06031196 -0.0347727  -0.07506503 ...,  0.03852069  0.2454992
   0.20753239]]
Progress: 6.2% ... Training loss: 0.297 ... Validation loss: 0.454[[ 0.32788354]
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[[ 0.05472254 -0.14282265  0.03395495 ..., -0.13460516  0.15768681
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   0.20682375]]
Progress: 6.2% ... Training loss: 0.303 ... Validation loss: 0.464[[ 0.31087859]
 [-0.29661618]
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[[ 0.05360117 -0.14187264  0.03668901 ..., -0.13435043  0.1548124
  -0.1770035 ]
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   0.20660967]]
Progress: 6.3% ... Training loss: 0.309 ... Validation loss: 0.463[[ 0.3171747 ]
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[[ 0.05445926 -0.14264409  0.03476256 ..., -0.13460189  0.15684082
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  -0.23352963]
 [ 0.06027712 -0.0347102  -0.07492158 ...,  0.03853986  0.24574207
   0.20762985]]
Progress: 6.3% ... Training loss: 0.294 ... Validation loss: 0.453[[ 0.3193308 ]
 [-0.2898432 ]
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[[ 0.05483301 -0.1429699   0.03389539 ..., -0.13470402  0.15770058
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  -0.23354823]
 [ 0.06012645 -0.03456483 -0.07452727 ...,  0.03857811  0.24538449
   0.20789467]]
Progress: 6.3% ... Training loss: 0.292 ... Validation loss: 0.454[[ 0.31731457]
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[[ 0.05419238 -0.14233817  0.03565075 ..., -0.13454092  0.15616122
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   0.20862422]]
Progress: 6.3% ... Training loss: 0.294 ... Validation loss: 0.455[[ 0.33089413]
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[[ 0.05544123 -0.14344167  0.0326728  ..., -0.13486637  0.15934557
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   0.2069136 ]]
Progress: 6.3% ... Training loss: 0.316 ... Validation loss: 0.488[[ 0.31365756]
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[[ 0.05439978 -0.14253186  0.03533068 ..., -0.13465213  0.15680484
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   0.2096828 ]]
Progress: 6.3% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.33121857]
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[[ 0.05517411 -0.14324721  0.03340693 ..., -0.13486943  0.15879057
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   0.20800037]]
Progress: 6.3% ... Training loss: 0.314 ... Validation loss: 0.488[[ 0.31306785]
 [-0.29603522]
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[[ 0.05435615 -0.14255272  0.03554499 ..., -0.13468952  0.15652603
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   0.20905631]]
Progress: 6.3% ... Training loss: 0.302 ... Validation loss: 0.457[[ 0.31657878]
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[[ 0.05432189 -0.14249438  0.03571079 ..., -0.13467244  0.15639878
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   0.20893319]]
Progress: 6.3% ... Training loss: 0.293 ... Validation loss: 0.452[[ 0.31619906]
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[[ 0.05425308 -0.14240456  0.03591705 ..., -0.13465368  0.15615252
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  -0.2340005 ]
 [ 0.0593305  -0.03385395 -0.07241799 ...,  0.03872176  0.24441277
   0.20974554]]
Progress: 6.3% ... Training loss: 0.293 ... Validation loss: 0.454[[ 0.31566493]
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[[ 0.05428648 -0.14240004  0.03594212 ..., -0.13465401  0.15608927
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 [ 0.05952405 -0.03403341 -0.07293909 ...,  0.0386743   0.24496014
   0.20918098]]
Progress: 6.3% ... Training loss: 0.293 ... Validation loss: 0.454[[ 0.31639503]
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[[ 0.05420439 -0.14229801  0.03628064 ..., -0.13462167  0.15573127
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 [-0.19094189 -0.18389233 -0.12041666 ...,  0.10699207 -0.05330581
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 [ 0.0594237  -0.03392232 -0.07264218 ...,  0.03870265  0.24484541
   0.20944575]]
Progress: 6.3% ... Training loss: 0.292 ... Validation loss: 0.454[[ 0.32560141]
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[[ 0.05524428 -0.14329338  0.03367035 ..., -0.13489851  0.15842686
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 [-0.19033471 -0.18446141 -0.12194028 ...,  0.10684134 -0.05196612
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 [ 0.05921737 -0.03373758 -0.07204664 ...,  0.0387541   0.24441247
   0.20997778]]
Progress: 6.3% ... Training loss: 0.305 ... Validation loss: 0.473[[ 0.30830777]
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[[ 0.05387153 -0.14207995  0.03719278 ..., -0.13459906  0.15476589
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   0.21238415]]
Progress: 6.3% ... Training loss: 0.308 ... Validation loss: 0.463[[ 0.32583011]
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[[ 0.05516177 -0.14336391  0.03375478 ..., -0.13497043  0.15845619
  -0.18103702]
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   0.21027159]]
Progress: 6.3% ... Training loss: 0.303 ... Validation loss: 0.473[[ 0.30819277]
 [-0.29852491]
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[[ 0.05386823 -0.14218548  0.037089   ..., -0.13466882  0.15547784
  -0.17772944]
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  -0.23277385]
 [ 0.05912865 -0.03371206 -0.07203691 ...,  0.0387345   0.24466241
   0.21008306]]
Progress: 6.4% ... Training loss: 0.310 ... Validation loss: 0.460[[ 0.3201302 ]
 [-0.28800375]
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[[ 0.05450183 -0.14274939  0.03567976 ..., -0.13482927  0.15698613
  -0.17918402]
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 [-0.19079052 -0.18409983 -0.120877   ...,  0.10692276 -0.0533004
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  -0.23348352]
 [ 0.0589416  -0.03353239 -0.07155623 ...,  0.03878746  0.24430275
   0.21059836]]
Progress: 6.4% ... Training loss: 0.294 ... Validation loss: 0.449[[ 0.31756753]
 [-0.2898343 ]
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 [ 0.42303266]
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[[ 0.05424258 -0.14250092  0.0363208  ..., -0.13475775  0.15639106
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  -0.23343528]
 [ 0.05908665 -0.0336642  -0.0719707  ...,  0.038757    0.24477558
   0.21018719]]
Progress: 6.4% ... Training loss: 0.292 ... Validation loss: 0.449[[ 0.31766409]
 [-0.29001417]
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[[ 0.0540288  -0.14228116  0.03685096 ..., -0.13470607  0.15586464
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  -0.23259674]
 [ 0.05929971 -0.03383126 -0.07250113 ...,  0.03872057  0.24543128
   0.20966894]]
Progress: 6.4% ... Training loss: 0.292 ... Validation loss: 0.446[[ 0.31928763]
 [-0.28727849]
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[[ 0.05379347 -0.14205274  0.03752175 ..., -0.13464694  0.15506477
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  -0.23224927]
 [ 0.05927689 -0.03380132 -0.07244281 ...,  0.03872781  0.245471
   0.20976619]]
Progress: 6.4% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.32424048]
 [-0.28444559]
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 [ 1.20866314]
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[[ 0.05409115 -0.14233956  0.03673309 ..., -0.13472273  0.15596816
  -0.17841005]
 [ 0.0369159   0.0503836   0.12371975 ..., -0.24338892 -0.05048582
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   0.20833767]]
Progress: 6.4% ... Training loss: 0.296 ... Validation loss: 0.458[[ 0.31642856]
 [-0.29211464]
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[[ 0.05301728 -0.14140181  0.03943402 ..., -0.13448779  0.15312582
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  -0.23188904]
 [ 0.05931715 -0.03384976 -0.07254401 ...,  0.0387131   0.24575493
   0.20966647]]
Progress: 6.4% ... Training loss: 0.294 ... Validation loss: 0.452[[ 0.31898331]
 [-0.29058939]
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[[ 0.05346326 -0.14183808  0.03829041 ..., -0.13461481  0.15432163
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 [-0.19125013 -0.18370402 -0.1197074  ...,  0.10701784 -0.05482317
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  -0.23243683]
 [ 0.05944124 -0.03397347 -0.07288005 ...,  0.03868061  0.24621808
   0.20932813]]
Progress: 6.4% ... Training loss: 0.292 ... Validation loss: 0.450[[ 0.31822594]
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[[ 0.05264262 -0.14104723  0.04042486 ..., -0.13441609  0.15237016
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 [-0.19121287 -0.1837293  -0.11978471 ...,  0.10700979 -0.0547276
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  -0.23282347]
 [ 0.05940797 -0.03396968 -0.07287345 ...,  0.03867864  0.24628359
   0.20917826]]
Progress: 6.4% ... Training loss: 0.293 ... Validation loss: 0.451[[ 0.32427815]
 [-0.28824475]
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[[ 0.0532591  -0.14162399  0.03897712 ..., -0.13457682  0.15396437
  -0.17711568]
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 [-0.19078767 -0.18412445 -0.12075718 ...,  0.10689788 -0.05373211
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  -0.23282776]
 [ 0.05965908 -0.03419726 -0.07351958 ...,  0.03861989  0.24690218
   0.2085768 ]]
Progress: 6.4% ... Training loss: 0.294 ... Validation loss: 0.451[[ 0.32043412]
 [-0.29239416]
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[[ 0.05280264 -0.14123067  0.04016397 ..., -0.13447084  0.15287286
  -0.17606566]
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 ..., 
 [-0.19116756 -0.18378635 -0.11979041 ...,  0.10698752 -0.05471864
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  -0.23272399]
 [ 0.05905073 -0.03363049 -0.07200178 ...,  0.03876717  0.24549283
   0.20990434]]
Progress: 6.4% ... Training loss: 0.293 ... Validation loss: 0.452[[ 0.3279357 ]
 [-0.28571695]
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[[ 0.05382579 -0.14214386  0.03765847 ..., -0.13471601  0.15512781
  -0.17844606]
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   0.12782014]
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 ..., 
 [-0.19102367 -0.18391169 -0.12017466 ...,  0.10694925 -0.0543889
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   0.20931393]]
Progress: 6.4% ... Training loss: 0.300 ... Validation loss: 0.456[[ 0.32226384]
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[[ 0.05366072 -0.14201961  0.03809038 ..., -0.13468424  0.15476155
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 [ 0.03722041  0.05011364  0.12292128 ..., -0.2434656  -0.04959834
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 [-0.19130188 -0.18367689 -0.1194554  ...,  0.1070127  -0.05507483
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  -0.23319106]
 [ 0.05973961 -0.0342064  -0.07357964 ...,  0.03862126  0.24763073
   0.20836163]]
Progress: 6.4% ... Training loss: 0.292 ... Validation loss: 0.446[[ 0.32028714]
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[[ 0.05313107 -0.14150458  0.0395322  ..., -0.13454518  0.15330985
  -0.17652008]
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   0.20812479]]
Progress: 6.4% ... Training loss: 0.293 ... Validation loss: 0.448[[ 0.31237007]
 [-0.2985629 ]
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 [-0.84140984]
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 [ 1.19846614]
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[[ 0.0522246  -0.14061692  0.04204589 ..., -0.13431876  0.15086126
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   0.21017892]]
Progress: 6.4% ... Training loss: 0.309 ... Validation loss: 0.467[[ 0.33702612]
 [-0.27724114]
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 [ 1.21780782]
 [ 0.43750674]
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[[ 0.05361108 -0.14189624  0.03863035 ..., -0.13471006  0.15435368
  -0.17761056]
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  -0.2350975 ]
 [ 0.05919956 -0.03369214 -0.0722749  ...,  0.03872629  0.24653107
   0.20932899]]
Progress: 6.5% ... Training loss: 0.335 ... Validation loss: 0.500[[ 0.3290797 ]
 [-0.28544193]
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[[ 0.05337576 -0.14172098  0.03922177 ..., -0.1346683   0.15392052
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 [ 0.05966923 -0.03410258 -0.07341059 ...,  0.03863786  0.24773264
   0.20821164]]
Progress: 6.5% ... Training loss: 0.301 ... Validation loss: 0.457[[ 0.31214367]
 [-0.30128479]
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[[ 0.0521883  -0.1407077   0.04201788 ..., -0.1344206   0.15107089
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  -0.23226184]
 [ 0.05931081 -0.03378331 -0.07251056 ...,  0.03872093  0.24691679
   0.20902941]]
Progress: 6.5% ... Training loss: 0.313 ... Validation loss: 0.469[[ 0.32506622]
 [-0.29022446]
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[[ 0.053002   -0.141537    0.03989835 ..., -0.1346651   0.15310482
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  -0.23202031]
 [ 0.05986346 -0.0343418  -0.07399918 ...,  0.03855877  0.24849974
   0.20752136]]
Progress: 6.5% ... Training loss: 0.293 ... Validation loss: 0.449[[ 0.33059221]
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[[ 0.05383548 -0.14232055  0.03773965 ..., -0.1348785   0.15533224
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 [ 0.03741829  0.0499202   0.12243277 ..., -0.24352326 -0.04904827
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 [ 0.05958274 -0.03405239 -0.07323726 ...,  0.03862941  0.24793669
   0.20819824]]
Progress: 6.5% ... Training loss: 0.301 ... Validation loss: 0.455[[ 0.31858014]
 [-0.29659606]
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[[ 0.05286607 -0.14147824  0.04017746 ..., -0.13467823  0.15295516
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  -0.23123802]
 [ 0.0587725  -0.03332533 -0.07119557 ...,  0.03880608  0.2461103
   0.21004442]]
Progress: 6.5% ... Training loss: 0.297 ... Validation loss: 0.452[[ 0.32608355]
 [-0.29003836]
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[[ 0.05341155 -0.14199917  0.03902019 ..., -0.13481977  0.15423496
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   0.21048097]]
Progress: 6.5% ... Training loss: 0.293 ... Validation loss: 0.450[[ 0.32234703]
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[[ 0.05281681 -0.14146764  0.0405526  ..., -0.13468482  0.15256655
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 [ 0.05879214 -0.03333472 -0.07103418 ...,  0.03880976  0.24636989
   0.21011815]]
Progress: 6.5% ... Training loss: 0.292 ... Validation loss: 0.451[[ 0.31996823]
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[[ 0.05277803 -0.14140828  0.04066589 ..., -0.1346685   0.15245106
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 [-0.19114721 -0.18388874 -0.11994221 ...,  0.10693959 -0.05507703
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  -0.2322329 ]
 [ 0.05883148 -0.03335965 -0.07113439 ...,  0.03880244  0.24671501
   0.21000012]]
Progress: 6.5% ... Training loss: 0.294 ... Validation loss: 0.453[[ 0.32313234]
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[[ 0.0526269  -0.14127347  0.04118362 ..., -0.1346338   0.15205112
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 [-0.19120602 -0.18382872 -0.11979603 ...,  0.10695514 -0.05528171
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  -0.23241931]
 [ 0.05867809 -0.03319554 -0.07070183 ...,  0.03884546  0.24650275
   0.21039614]]
Progress: 6.5% ... Training loss: 0.292 ... Validation loss: 0.455[[ 0.32969658]
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[[ 0.05285402 -0.14144757  0.04071582 ..., -0.13468098  0.15242552
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   0.21006163]]
Progress: 6.5% ... Training loss: 0.297 ... Validation loss: 0.465[[ 0.3186222 ]
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[[ 0.05245321 -0.14107047  0.04172751 ..., -0.1345785   0.15142548
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   0.12870031]
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 [-0.19106496 -0.18395794 -0.12012048 ...,  0.10691633 -0.05497963
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   0.21034492]]
Progress: 6.5% ... Training loss: 0.296 ... Validation loss: 0.456[[ 0.32218904]
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[[ 0.05277694 -0.14139715  0.04085659 ..., -0.13466401  0.15229675
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 [ 0.03666332  0.05058635  0.12419333 ..., -0.2433553  -0.05077123
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 [ 0.0585483  -0.03305488 -0.07030534 ...,  0.0388924   0.24638564
   0.21087314]]
Progress: 6.5% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.32288282]
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 [ 0.13651895]
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[[ 0.05239267 -0.14100654  0.04190454 ..., -0.13455115  0.15129565
  -0.17575475]
 [ 0.03647337  0.05075314  0.12466547 ..., -0.24330677 -0.05126123
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  -0.23245202]
 [ 0.0584425  -0.03294381 -0.07003659 ...,  0.03892265  0.24620078
   0.2111728 ]]
Progress: 6.5% ... Training loss: 0.291 ... Validation loss: 0.453[[ 0.3283013 ]
 [-0.29050937]
 [-0.79949285]
 [-0.82394229]
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 [ 1.21380698]
 [ 0.42406796]
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 [ 1.10301422]
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 [ 0.03662831]
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[[  5.25978273e-02  -1.41189712e-01   4.14469974e-02 ...,  -1.34610003e-01
    1.51957008e-01  -1.76222151e-01]
 [  3.64429098e-02   5.07804176e-02   1.24728694e-01 ...,  -2.43304212e-01
   -5.11808995e-02   1.29464868e-01]
 [ -3.07371765e-02   1.10155687e-02  -5.91323606e-02 ...,   1.63830951e-01
    1.66810410e-05   2.77426790e-01]
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 [ -1.90730070e-01  -1.84248410e-01  -1.20885657e-01 ...,   1.06831770e-01
   -5.42663642e-02  -3.24941168e-02]
 [ -2.79307115e-01  -2.21829555e-01  -4.42231586e-02 ...,  -1.17055772e-01
   -1.21721017e-02  -2.32881561e-01]
 [  5.85666525e-02  -3.30685020e-02  -7.04242164e-02 ...,   3.88947371e-02
    2.46662455e-01   2.10810617e-01]]
Progress: 6.5% ... Training loss: 0.293 ... Validation loss: 0.456[[ 0.33357161]
 [-0.2862012 ]
 [-0.79696931]
 [-0.82136982]
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 [ 1.21721801]
 [ 0.42778798]
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[[ 0.0531152  -0.14166873  0.04023853 ..., -0.13471086  0.15320904
  -0.17771265]
 [ 0.03636814  0.05084731  0.12490773 ..., -0.2432884  -0.05137547
   0.12964066]
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 [-0.19059395 -0.18436893 -0.12119937 ...,  0.10679936 -0.05396677
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  -0.23255082]
 [ 0.05887794 -0.03334538 -0.07118412 ...,  0.03883308  0.24749536
   0.21001112]]
Progress: 6.6% ... Training loss: 0.304 ... Validation loss: 0.468[[ 0.32256988]
 [-0.29700399]
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 [-0.83210524]
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 [ 1.21230985]
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[[ 0.0530955  -0.14167275  0.04030033 ..., -0.1347215   0.1530481
  -0.17772021]
 [ 0.03632982  0.0508798   0.12499585 ..., -0.24328073 -0.05145333
   0.12975937]
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  -0.2317426 ]
 [ 0.05862385 -0.03311152 -0.0705734  ...,  0.03888448  0.2471373
   0.21060227]]
Progress: 6.6% ... Training loss: 0.293 ... Validation loss: 0.450[[ 0.32947414]
 [-0.29067642]
 [-0.80078028]
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 [ 1.21438577]
 [ 0.42450587]
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[[ 0.05321903 -0.14179571  0.04011726 ..., -0.13474712  0.15314343
  -0.17770985]
 [ 0.03645008  0.05076821  0.12468672 ..., -0.24330837 -0.05113935
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  -0.23248539]
 [ 0.05908954 -0.03355303 -0.07172988 ...,  0.03876847  0.2482915
   0.20940385]]
Progress: 6.6% ... Training loss: 0.293 ... Validation loss: 0.460[[ 0.33090487]
 [-0.28988408]
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 [ 1.21878094]
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[[ 0.05345148 -0.14200558  0.03951189 ..., -0.13480443  0.15385416
  -0.17814195]
 [ 0.03635023  0.05085567  0.12481936 ..., -0.24328449 -0.05133512
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 [-0.19041165 -0.18455714 -0.12181082 ...,  0.10674601 -0.05374406
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  -0.23214428]
 [ 0.0591079  -0.03355524 -0.07170632 ...,  0.03877112  0.24854286
   0.20929727]]
Progress: 6.6% ... Training loss: 0.297 ... Validation loss: 0.458[[ 0.33528452]
 [-0.28637499]
 [-0.79444401]
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 [ 1.22033366]
 [ 0.42960951]
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[[ 0.05406399 -0.14254657  0.03813824 ..., -0.13495678  0.15537765
  -0.17956667]
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 [-0.18991731 -0.18498631 -0.12297191 ...,  0.10663519 -0.05263274
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  -0.23177347]
 [ 0.05986247 -0.03425484 -0.07350319 ...,  0.03860065  0.25042233
   0.20741678]]
Progress: 6.6% ... Training loss: 0.308 ... Validation loss: 0.472[[ 0.32043373]
 [-0.2993537 ]
 [-0.80587715]
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[[ 0.05307736 -0.14163871  0.04075164 ..., -0.13475162  0.15276197
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 [-0.19094406 -0.18411566 -0.12055819 ...,  0.10683884 -0.0551782
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  -0.23182299]
 [ 0.06001918 -0.03439768 -0.0738883  ...,  0.038572    0.25085776
   0.20703338]]
Progress: 6.6% ... Training loss: 0.295 ... Validation loss: 0.454[[ 0.32189288]
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[[ 0.05293996 -0.14143142  0.04123315 ..., -0.13469712  0.15263321
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 [ 0.03612411  0.0510582   0.1253536  ..., -0.24323502 -0.05186892
   0.1303483 ]
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   0.27761938]
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 [-0.19080953 -0.18424729 -0.120918   ...,  0.10680005 -0.05474551
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  -0.2320621 ]
 [ 0.05992898 -0.03426336 -0.07358474 ...,  0.03860612  0.25080058
   0.20722559]]
Progress: 6.6% ... Training loss: 0.293 ... Validation loss: 0.452[[ 0.31104212]
 [-0.30518476]
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[[ 0.05129369 -0.13985801  0.04541907 ..., -0.13429047  0.14866994
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 [-0.19059053 -0.18445165 -0.1214416  ...,  0.10674856 -0.05423753
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  -0.23136692]
 [ 0.05897578 -0.03332668 -0.07117953 ...,  0.03884743  0.24860812
   0.20968438]]
Progress: 6.6% ... Training loss: 0.323 ... Validation loss: 0.487[[ 0.335811  ]
 [-0.28206691]
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[[ 0.05291356 -0.14147781  0.04131289 ..., -0.13473855  0.15266322
  -0.17672882]
 [ 0.0361337   0.05104208  0.12529235 ..., -0.24324221 -0.05181843
   0.13031113]
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   0.28147966]
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 [-0.18996227 -0.18507774 -0.12307346 ...,  0.1065741  -0.05268715
  -0.03458999]
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  -0.2321912 ]
 [ 0.05919593 -0.03353268 -0.0717426  ...,  0.03878773  0.2493107
   0.20915984]]
Progress: 6.6% ... Training loss: 0.316 ... Validation loss: 0.482[[ 0.32355808]
 [-0.29264181]
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[[ 0.05243166 -0.14106698  0.04251264 ..., -0.13463932  0.15156665
  -0.17562604]
 [ 0.03629794  0.05091392  0.12490889 ..., -0.24327221 -0.051405
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 [-0.19020277 -0.18487113 -0.12251511 ...,  0.10662135 -0.05330377
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  -0.2312908 ]
 [ 0.05920181 -0.0335247  -0.07172625 ...,  0.0387937   0.24946202
   0.20913422]]
Progress: 6.6% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.3306265 ]
 [-0.2870437 ]
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[[ 0.05285639 -0.14145568  0.04144221 ..., -0.13472731  0.15281869
  -0.17663074]
 [ 0.03641622  0.05080916  0.12462025 ..., -0.24329511 -0.05109497
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 ..., 
 [-0.18985324 -0.18519387 -0.12337092 ...,  0.10653499 -0.05252994
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 [-0.27991953 -0.2213464  -0.04289776 ..., -0.11695434 -0.01356107
  -0.23143991]
 [ 0.05931133 -0.03362212 -0.07206923 ...,  0.03877988  0.24987327
   0.20879213]]
Progress: 6.6% ... Training loss: 0.300 ... Validation loss: 0.459[[ 0.32660376]
 [-0.29167353]
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[[ 0.05256884 -0.14122474  0.04217993 ..., -0.13468212  0.15212192
  -0.17598484]
 [ 0.03634776  0.05086083  0.12478495 ..., -0.24328322 -0.05125753
   0.12975524]
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 [-0.18979236 -0.18525244 -0.12353152 ...,  0.10652265 -0.05241321
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  -0.23062742]
 [ 0.05968921 -0.03396621 -0.07298274 ...,  0.03869903  0.25091847
   0.20786126]]
Progress: 6.6% ... Training loss: 0.292 ... Validation loss: 0.452[[ 0.32760831]
 [-0.29144522]
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[[ 0.05232984 -0.14101125  0.04282177 ..., -0.13463345  0.1515985
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   0.20656908]]
Progress: 6.6% ... Training loss: 0.294 ... Validation loss: 0.452[[ 0.32924425]
 [-0.28981226]
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 [ 0.42475345]
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[[ 0.05283237 -0.14143483  0.04180532 ..., -0.13474064  0.15260817
  -0.17676789]
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   0.20709966]]
Progress: 6.6% ... Training loss: 0.294 ... Validation loss: 0.454[[ 0.32586464]
 [-0.29326855]
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[[ 0.05198295 -0.14067737  0.0439651  ..., -0.13456561  0.15059561
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   0.20769774]]
Progress: 6.6% ... Training loss: 0.291 ... Validation loss: 0.453[[ 0.32793977]
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[[ 0.05212284 -0.1407995   0.04368809 ..., -0.1345956   0.15083736
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  -0.23236247]
 [ 0.05996301 -0.03421014 -0.07366585 ...,  0.03863601  0.25201452
   0.2071903 ]]
Progress: 6.7% ... Training loss: 0.291 ... Validation loss: 0.452[[ 0.32442661]
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[[ 0.05102129 -0.1398107   0.0464096  ..., -0.13435366  0.14826668
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 [ 0.05964545 -0.03390274 -0.07279376 ...,  0.03871528  0.25146067
   0.2080547 ]]
Progress: 6.7% ... Training loss: 0.295 ... Validation loss: 0.457[[ 0.33097793]
 [-0.29109721]
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[[ 0.0513821  -0.14018373  0.04563514 ..., -0.13443663  0.14899174
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   0.2074007 ]]
Progress: 6.7% ... Training loss: 0.291 ... Validation loss: 0.457[[ 0.33455906]
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[[ 0.05188631 -0.14064761  0.04448292 ..., -0.13455492  0.15023125
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   0.20713726]]
Progress: 6.7% ... Training loss: 0.294 ... Validation loss: 0.458[[ 0.32839582]
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[[ 0.05082738 -0.13967938  0.0471388  ..., -0.13432221  0.14766831
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   0.20834524]]
Progress: 6.7% ... Training loss: 0.292 ... Validation loss: 0.455[[ 0.32947631]
 [-0.29199744]
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[[ 0.05130198 -0.14004942  0.04617594 ..., -0.13439325  0.14872732
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   0.20792511]]
Progress: 6.7% ... Training loss: 0.292 ... Validation loss: 0.452[[ 0.33850984]
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[[ 0.05252763 -0.14113196  0.04358812 ..., -0.13466291  0.15136149
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   0.20665364]]
Progress: 6.7% ... Training loss: 0.304 ... Validation loss: 0.469[[ 0.3198558 ]
 [-0.30023425]
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[[ 0.05051694 -0.13940963  0.04835582 ..., -0.13425932  0.14662833
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 [ 0.05925659 -0.03360862 -0.07196522 ...,  0.03877492  0.25134859
   0.20866173]]
Progress: 6.7% ... Training loss: 0.312 ... Validation loss: 0.475[[ 0.33915902]
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[[ 0.05209296 -0.14092372  0.04443077 ..., -0.13468206  0.15041304
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 [ 0.03628689  0.05093688  0.12482212 ..., -0.24325558 -0.05127038
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 [ 0.05950034 -0.03383511 -0.07256132 ...,  0.03871029  0.25204674
   0.20805153]]
Progress: 6.7% ... Training loss: 0.304 ... Validation loss: 0.469[[ 0.32298258]
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[[ 0.05071876 -0.13975822  0.04773455 ..., -0.13439334  0.14721271
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 [ 0.03621959  0.05099111  0.1249804  ..., -0.2432414  -0.05143778
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 [-0.19094255 -0.18433618 -0.1208443  ...,  0.10672397 -0.05573748
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  -0.23298372]
 [ 0.05872749 -0.03317059 -0.07073725 ...,  0.03886976  0.25042379
   0.20979073]]
Progress: 6.7% ... Training loss: 0.302 ... Validation loss: 0.466[[ 0.33448508]
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[[ 0.05122347 -0.14018127  0.04653046 ..., -0.13450406  0.1482557
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 [ 0.05863947 -0.03307483 -0.07050876 ...,  0.038892    0.2502322
   0.20995354]]
Progress: 6.7% ... Training loss: 0.295 ... Validation loss: 0.463[[ 0.32462704]
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[[ 0.05080147 -0.13974683  0.04762313 ..., -0.1344039   0.14719062
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   0.2089668 ]]
Progress: 6.7% ... Training loss: 0.294 ... Validation loss: 0.460[[ 0.3200612 ]
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[[ 0.0509683  -0.1399016   0.04714532 ..., -0.1344539   0.14755411
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   0.21022478]]
Progress: 6.7% ... Training loss: 0.303 ... Validation loss: 0.471[[ 0.3269173 ]
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[[ 0.05062384 -0.13958857  0.04809498 ..., -0.13437182  0.14689614
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   0.21101109]]
Progress: 6.7% ... Training loss: 0.293 ... Validation loss: 0.460[[ 0.31386095]
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[[ 0.04987274 -0.13894039  0.04996297 ..., -0.13419038  0.14514222
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  -0.2343576 ]
 [ 0.05723308 -0.03171198 -0.06718561 ...,  0.03927127  0.24748918
   0.21345713]]
Progress: 6.7% ... Training loss: 0.334 ... Validation loss: 0.504[[ 0.34686509]
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[[ 0.05247604 -0.14155006  0.04304897 ..., -0.13494905  0.15199698
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   0.21043674]]
Progress: 6.8% ... Training loss: 0.345 ... Validation loss: 0.509[[ 0.31930329]
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[[ 0.05113637 -0.14046453  0.04613111 ..., -0.13472161  0.14865988
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  -0.23454795]
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   0.21177291]]
Progress: 6.8% ... Training loss: 0.311 ... Validation loss: 0.477[[ 0.33253429]
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[[ 0.05246738 -0.1417139   0.04302349 ..., -0.13506606  0.1518194
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 [ 0.05780547 -0.0323369  -0.06884023 ...,  0.03905605  0.24942684
   0.21176112]]
Progress: 6.8% ... Training loss: 0.292 ... Validation loss: 0.456[[ 0.31670883]
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   0.21334817]]
Progress: 6.8% ... Training loss: 0.320 ... Validation loss: 0.486[[ 0.34462157]
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   0.21082863]]
Progress: 6.8% ... Training loss: 0.335 ... Validation loss: 0.497[[ 0.31123841]
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[[ 0.051092   -0.14079172  0.04612582 ..., -0.1349872   0.14879009
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   0.21157845]]
Progress: 6.8% ... Training loss: 0.346 ... Validation loss: 0.517[[ 0.33595986]
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[[ 0.05303554 -0.14274425  0.04115018 ..., -0.13557478  0.1538079
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   0.2088594 ]]
Progress: 6.8% ... Training loss: 0.299 ... Validation loss: 0.465[[ 0.31442312]
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[[ 0.05234221 -0.14213362  0.04289251 ..., -0.13543083  0.15193573
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   0.20972434]]
Progress: 6.8% ... Training loss: 0.326 ... Validation loss: 0.490[[ 0.32964932]
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[[ 0.05313623 -0.14291091  0.04087152 ..., -0.13566952  0.15398786
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   0.20843865]]
Progress: 6.8% ... Training loss: 0.291 ... Validation loss: 0.462[[ 0.3284423 ]
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[[ 0.05306494 -0.14280808  0.04117648 ..., -0.13564323  0.15375507
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   0.20983694]]
Progress: 6.8% ... Training loss: 0.290 ... Validation loss: 0.457[[ 0.33017288]
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[[ 0.05293956 -0.14270347  0.04154818 ..., -0.13562555  0.15373064
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 [ 0.05821149 -0.03294924 -0.07030621 ...,  0.0388099   0.25135575
   0.2101012 ]]
Progress: 6.8% ... Training loss: 0.290 ... Validation loss: 0.455[[ 0.33099751]
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[[ 0.05278433 -0.14260923  0.04179678 ..., -0.13559266  0.1533038
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   0.20894235]]
Progress: 6.8% ... Training loss: 0.290 ... Validation loss: 0.456[[ 0.32224227]
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[[ 0.05211245 -0.14196963  0.0435849  ..., -0.13543166  0.15157074
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   0.20923563]]
Progress: 6.8% ... Training loss: 0.296 ... Validation loss: 0.461[[ 0.32656495]
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[[ 0.05269516 -0.14245487  0.04222567 ..., -0.13555791  0.15321155
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   0.20853982]]
Progress: 6.8% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.32541186]
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[[ 0.05303842 -0.14280014  0.04129337 ..., -0.13565669  0.15422554
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   0.20766292]]
Progress: 6.8% ... Training loss: 0.290 ... Validation loss: 0.455[[ 0.32534213]
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[[ 0.05280507 -0.14257288  0.04201301 ..., -0.13558734  0.15355562
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   0.2081017 ]]
Progress: 6.9% ... Training loss: 0.290 ... Validation loss: 0.457[[ 0.33046415]
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 [ 0.05886207 -0.03352966 -0.0719523  ...,  0.03865459  0.25358178
   0.20840599]]
Progress: 6.9% ... Training loss: 0.292 ... Validation loss: 0.456[[ 0.3239149 ]
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   0.20757945]]
Progress: 6.9% ... Training loss: 0.292 ... Validation loss: 0.457[[ 0.32829082]
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   0.2062521 ]]
Progress: 6.9% ... Training loss: 0.290 ... Validation loss: 0.456[[ 0.33365541]
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   0.20580184]]
Progress: 6.9% ... Training loss: 0.294 ... Validation loss: 0.458[[ 0.32361727]
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[[ 0.05216174 -0.14206425  0.04354498 ..., -0.13547795  0.152035
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   0.20696427]]
Progress: 6.9% ... Training loss: 0.294 ... Validation loss: 0.461[[ 0.3290181 ]
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[[ 0.05272085 -0.1426145   0.04206782 ..., -0.13563378  0.15352013
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   0.20683198]]
Progress: 6.9% ... Training loss: 0.289 ... Validation loss: 0.455[[ 0.31970767]
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[[ 0.0516211  -0.14159351  0.04483603 ..., -0.13534999  0.15074654
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 [ 0.05965006 -0.03422629 -0.07396305 ...,  0.03846279  0.25648137
   0.20665999]]
Progress: 6.9% ... Training loss: 0.303 ... Validation loss: 0.469[[ 0.32623242]
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[[ 0.05137454 -0.14133928  0.04546533 ..., -0.13527487  0.1501507
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 [ 0.05993736 -0.03449546 -0.0746981  ...,  0.0383957   0.25729691
   0.20590033]]
Progress: 6.9% ... Training loss: 0.291 ... Validation loss: 0.457[[ 0.33298656]
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[[ 0.05199399 -0.14190567  0.0439363  ..., -0.13543052  0.15175303
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   0.2057994 ]]
Progress: 6.9% ... Training loss: 0.292 ... Validation loss: 0.457[[ 0.32825749]
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[[ 0.05177558 -0.14168753  0.0445632  ..., -0.13537955  0.15134973
  -0.175445  ]
 [ 0.03587106  0.05125433  0.12552426 ..., -0.24319801 -0.05156945
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   0.20632595]]
Progress: 6.9% ... Training loss: 0.290 ... Validation loss: 0.455[[ 0.32026691]
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[[ 0.05079525 -0.14078472  0.04696493 ..., -0.13515407  0.14917527
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 [ 0.05932626 -0.03392194 -0.07316337 ...,  0.03855266  0.25623009
   0.20742399]]
Progress: 6.9% ... Training loss: 0.302 ... Validation loss: 0.467[[ 0.32703992]
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[[ 0.05125231 -0.1411852   0.04603398 ..., -0.13527289  0.15024815
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   0.20691556]]
Progress: 6.9% ... Training loss: 0.289 ... Validation loss: 0.455[[ 0.32271768]
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[[ 0.05127542 -0.1412022   0.04597154 ..., -0.13526295  0.15038494
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   0.20603427]]
Progress: 6.9% ... Training loss: 0.292 ... Validation loss: 0.458[[ 0.32952182]
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[[ 0.0516674  -0.14156144  0.0449872  ..., -0.13536267  0.15122266
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   0.20626226]]
Progress: 6.9% ... Training loss: 0.290 ... Validation loss: 0.456[[ 0.33186833]
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[[ 0.05193031 -0.14173459  0.04441776 ..., -0.13542389  0.15211223
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 [ 0.05918378 -0.03376599 -0.07299123 ...,  0.03859949  0.25683079
   0.2076041 ]]
Progress: 7.0% ... Training loss: 0.294 ... Validation loss: 0.455[[ 0.32259236]
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[[ 0.05113588 -0.14103654  0.0463515  ..., -0.1352527   0.15012289
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   0.20787005]]
Progress: 7.0% ... Training loss: 0.294 ... Validation loss: 0.457[[ 0.33409144]
 [-0.28401922]
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[[ 0.052296   -0.14211627  0.04359965 ..., -0.13553892  0.15287253
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   0.20535074]]
Progress: 7.0% ... Training loss: 0.297 ... Validation loss: 0.465[[ 0.32862062]
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[[ 0.05265584 -0.14240669  0.04286005 ..., -0.13560556  0.15342346
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   0.20639601]]
Progress: 7.0% ... Training loss: 0.289 ... Validation loss: 0.454[[ 0.32655657]
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[[ 0.05312459 -0.14282233  0.04186179 ..., -0.13571615  0.15440152
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   0.20627031]]
Progress: 7.0% ... Training loss: 0.290 ... Validation loss: 0.456[[ 0.33208187]
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[[ 0.05365642 -0.14332339  0.04055271 ..., -0.13584942  0.15565554
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   0.20660004]]
Progress: 7.0% ... Training loss: 0.295 ... Validation loss: 0.468[[ 0.34056676]
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[[ 0.05492624 -0.14440755  0.03762791 ..., -0.13614955  0.15865321
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   0.20564469]]
Progress: 7.0% ... Training loss: 0.325 ... Validation loss: 0.495[[ 0.3242257 ]
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[[ 0.0542238  -0.14380622  0.03922291 ..., -0.13599662  0.15689955
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 [ 0.06018399 -0.03465429 -0.07554604 ...,  0.0383534   0.25998473
   0.2050814 ]]
Progress: 7.0% ... Training loss: 0.290 ... Validation loss: 0.453[[ 0.33058367]
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[[ 0.0544019  -0.14396894  0.03880024 ..., -0.13604234  0.15724543
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   0.20423645]]
Progress: 7.0% ... Training loss: 0.292 ... Validation loss: 0.458[[ 0.33458706]
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[[ 0.05558616 -0.14501763  0.0361684  ..., -0.13632527  0.16017353
  -0.1848189 ]
 [ 0.03630164  0.05091163  0.1243782  ..., -0.24330486 -0.05053539
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  -0.24082018]
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   0.20205799]]
Progress: 7.0% ... Training loss: 0.300 ... Validation loss: 0.468[[ 0.32772401]
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[[ 0.05581779 -0.14520525  0.03576949 ..., -0.13636736  0.16063343
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 [-0.19018642 -0.18525903 -0.1226846  ...,  0.10632958 -0.05584506
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   0.2034126 ]]
Progress: 7.0% ... Training loss: 0.289 ... Validation loss: 0.450[[ 0.32140991]
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[[ 0.05519259 -0.14463467  0.03733087 ..., -0.13621061  0.15896988
  -0.18379633]
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   0.20346924]]
Progress: 7.0% ... Training loss: 0.294 ... Validation loss: 0.454[[ 0.3329304 ]
 [-0.28934882]
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  -0.240659  ]
 [ 0.06112483 -0.03549033 -0.07770516 ...,  0.03812812  0.2627665
   0.20273125]]
Progress: 7.0% ... Training loss: 0.297 ... Validation loss: 0.466[[ 0.31732598]
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[[ 0.05488197 -0.14436097  0.03813666 ..., -0.13619023  0.15810063
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 [ 0.06020553 -0.03466142 -0.0755042  ...,  0.03832201  0.26065532
   0.2048207 ]]
Progress: 7.0% ... Training loss: 0.301 ... Validation loss: 0.457[[ 0.33909042]
 [-0.28469674]
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[[ 0.05639835 -0.14587944  0.03422274 ..., -0.13661523  0.16204035
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  -0.24098962]
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   0.2032659 ]]
Progress: 7.0% ... Training loss: 0.319 ... Validation loss: 0.491[[ 0.31374242]
 [-0.30744633]
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[[ 0.05476761 -0.14450035  0.03805936 ..., -0.13629621  0.15790629
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 [ 0.06065766 -0.03510032 -0.07658197 ...,  0.03819649  0.26190965
   0.203592  ]]
Progress: 7.1% ... Training loss: 0.319 ... Validation loss: 0.470[[ 0.32984158]
 [-0.29339593]
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[[ 0.05528829 -0.14501272  0.0367686  ..., -0.13644869  0.15919867
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  -0.2397278 ]
 [ 0.06066212 -0.0350916  -0.07660196 ...,  0.03819148  0.26209593
   0.20360523]]
Progress: 7.1% ... Training loss: 0.290 ... Validation loss: 0.455[[ 0.32257478]
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[[ 0.0539885  -0.14382386  0.03999312 ..., -0.13614263  0.15610127
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   0.20530851]]
Progress: 7.1% ... Training loss: 0.295 ... Validation loss: 0.454[[ 0.32964386]
 [-0.29234873]
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   0.20444897]]
Progress: 7.1% ... Training loss: 0.289 ... Validation loss: 0.452[[ 0.32857533]
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[[ 0.05458548 -0.14437916  0.03853415 ..., -0.13630424  0.15763971
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 [ 0.06049797 -0.03495484 -0.07634424 ...,  0.03821728  0.26223306
   0.20390805]]
Progress: 7.1% ... Training loss: 0.288 ... Validation loss: 0.451[[ 0.33735432]
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[[ 0.05525013 -0.14490143  0.03702679 ..., -0.13645957  0.15919011
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  -0.23891908]
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   0.2039204 ]]
Progress: 7.1% ... Training loss: 0.304 ... Validation loss: 0.477[[ 0.32838998]
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[[ 0.05446963 -0.14426311  0.03881653 ..., -0.13628321  0.1574257
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 [ 0.06032764 -0.0347618  -0.0758869  ...,  0.03826279  0.26187905
   0.20423356]]
Progress: 7.1% ... Training loss: 0.289 ... Validation loss: 0.452[[ 0.33368288]
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[[ 0.05537309 -0.14503394  0.0367193  ..., -0.13649063  0.15954591
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 [ 0.036877    0.05043143  0.1229604  ..., -0.2434297  -0.04909554
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 [-0.19078438 -0.18492896 -0.1215727  ...,  0.10634476 -0.05766616
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  -0.23927924]
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   0.20292584]]
Progress: 7.1% ... Training loss: 0.296 ... Validation loss: 0.458[[ 0.33136892]
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[[ 0.05533373 -0.14496539  0.03691961 ..., -0.13648426  0.15948843
  -0.18517742]
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  -0.24003354]
 [ 0.06065565 -0.03503676 -0.07671178 ...,  0.03819123  0.26316308
   0.20352735]]
Progress: 7.1% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.32579172]
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[[ 0.05496181 -0.14465622  0.0378344  ..., -0.13639856  0.15856036
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 [ 0.0608822  -0.0352443  -0.07725286 ...,  0.03814291  0.26384786
   0.20291489]]
Progress: 7.1% ... Training loss: 0.290 ... Validation loss: 0.446[[ 0.32559353]
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[[ 0.05469504 -0.14440421  0.03859793 ..., -0.1363378   0.15814404
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 [ 0.03688622  0.05042371  0.1229538  ..., -0.24343046 -0.04904026
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 [-0.19070593 -0.18500294 -0.12167809 ...,  0.10631871 -0.05763474
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   0.20309902]]
Progress: 7.1% ... Training loss: 0.290 ... Validation loss: 0.447[[ 0.3302983 ]
 [-0.29070898]
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[[ 0.05488094 -0.14457749  0.03818532 ..., -0.1363905   0.15871075
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   0.20308141]]
Progress: 7.1% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.3291711 ]
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   0.20380168]]
Progress: 7.1% ... Training loss: 0.289 ... Validation loss: 0.445[[ 0.33398272]
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[[ 0.0546876  -0.1444357   0.03870596 ..., -0.13636676  0.15856476
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   0.2043362 ]]
Progress: 7.1% ... Training loss: 0.292 ... Validation loss: 0.455[[ 0.32803428]
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[[ 0.05487212 -0.14463835  0.038178   ..., -0.13640349  0.15897742
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 [ 0.06027865 -0.03461031 -0.0757676  ...,  0.03830637  0.26316894
   0.20442743]]
Progress: 7.1% ... Training loss: 0.289 ... Validation loss: 0.447[[ 0.3338042 ]
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 [ 0.06067488 -0.03494998 -0.07678649 ...,  0.03821358  0.26421056
   0.20353653]]
Progress: 7.2% ... Training loss: 0.290 ... Validation loss: 0.454[[ 0.32301216]
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[[ 0.05377651 -0.14374429  0.04071926 ..., -0.13616482  0.15644539
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 [ 0.06028699 -0.03460856 -0.07587401 ...,  0.03830203  0.26334433
   0.20428093]]
Progress: 7.2% ... Training loss: 0.303 ... Validation loss: 0.458[[ 0.33686068]
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   0.202616  ]]
Progress: 7.2% ... Training loss: 0.292 ... Validation loss: 0.464[[ 0.33539475]
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[[ 0.05367669 -0.14366726  0.04102404 ..., -0.13616589  0.15623272
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   0.20337234]]
Progress: 7.2% ... Training loss: 0.291 ... Validation loss: 0.458[[ 0.33193966]
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[[ 0.05334888 -0.14337793  0.04191788 ..., -0.13609835  0.15520354
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   0.2033666 ]]
Progress: 7.2% ... Training loss: 0.288 ... Validation loss: 0.453[[ 0.33867084]
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[[ 0.05439921 -0.14431626  0.03954505 ..., -0.13636843  0.15762757
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   0.20297494]]
Progress: 7.2% ... Training loss: 0.296 ... Validation loss: 0.464[[ 0.32258233]
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[[ 0.0532518  -0.14333757  0.04221178 ..., -0.13612076  0.15493939
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 [ 0.06059407 -0.03491422 -0.07669736 ...,  0.03819434  0.26446134
   0.20341239]]
Progress: 7.2% ... Training loss: 0.303 ... Validation loss: 0.460[[ 0.34681122]
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[[ 0.05500297 -0.14497961  0.03791662 ..., -0.1365839   0.15910883
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 [ 0.06075317 -0.03504247 -0.0770529  ...,  0.038159    0.26490634
   0.20306944]]
Progress: 7.2% ... Training loss: 0.330 ... Validation loss: 0.498[[ 0.32892316]
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[[ 0.05388931 -0.14403577  0.04048971 ..., -0.13636271  0.15630908
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  -0.2382943 ]
 [ 0.06017903 -0.03453654 -0.0757875  ...,  0.03827771  0.26386909
   0.2043452 ]]
Progress: 7.2% ... Training loss: 0.289 ... Validation loss: 0.449[[ 0.33059387]
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[[ 0.05387683 -0.14398454  0.04064606 ..., -0.13634733  0.15623682
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 [ 0.03722087  0.05011229  0.12210392 ..., -0.24351058 -0.0481028
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 [-0.19011546 -0.18563693 -0.1230256  ...,  0.10611742 -0.05647005
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   0.20408497]]
Progress: 7.2% ... Training loss: 0.288 ... Validation loss: 0.451[[ 0.32568289]
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[[ 0.05378604 -0.14389707  0.04086851 ..., -0.13632861  0.1561396
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 [ 0.05989748 -0.03427887 -0.07516381 ...,  0.03835374  0.26345886
   0.20506416]]
Progress: 7.2% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.34641641]
 [-0.27949442]
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 [-0.80984853]
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 [ 1.26102186]
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[[ 0.05568304 -0.14569651  0.03623038 ..., -0.13683079  0.16088189
  -0.18607545]
 [ 0.03743133  0.04992415  0.1215711  ..., -0.24356161 -0.04756813
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  -0.2415087 ]
 [ 0.060377   -0.03473064 -0.07635424 ...,  0.03822831  0.26477641
   0.2039406 ]]
Progress: 7.2% ... Training loss: 0.330 ... Validation loss: 0.513[[ 0.32530741]
 [-0.29731318]
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 [ 0.41741896]
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[[ 0.05503033 -0.14516518  0.03784182 ..., -0.13669349  0.15922675
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 [ 0.05995514 -0.03437098 -0.07536603 ...,  0.0383158   0.26399303
   0.20493417]]
Progress: 7.2% ... Training loss: 0.291 ... Validation loss: 0.449[[ 0.3291754 ]
 [-0.29330235]
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[[ 0.05488688 -0.14499706  0.03826877 ..., -0.13665924  0.15879603
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  -0.24114072]
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   0.20440789]]
Progress: 7.2% ... Training loss: 0.288 ... Validation loss: 0.449[[ 0.32872221]
 [-0.29478766]
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[[ 0.05472726 -0.14485415  0.03857575 ..., -0.13661499  0.15850408
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  -0.241212  ]
 [ 0.06031099 -0.03470437 -0.07624665 ...,  0.03822855  0.26497767
   0.20407908]]
Progress: 7.2% ... Training loss: 0.289 ... Validation loss: 0.449[[ 0.32964908]
 [-0.29269428]
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[[ 0.05519812 -0.14527602  0.03749752 ..., -0.13672694  0.15966862
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   0.20474783]]
Progress: 7.3% ... Training loss: 0.287 ... Validation loss: 0.453[[ 0.32937355]
 [-0.29317268]
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[[ 0.05471646 -0.14485177  0.03873715 ..., -0.13659704  0.15865    -0.18354883]
 [ 0.03738683  0.04995516  0.12161858 ..., -0.24355812 -0.04769682
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 [ 0.05986699 -0.03428941 -0.07522954 ...,  0.03834048  0.26434607
   0.20519889]]
Progress: 7.3% ... Training loss: 0.289 ... Validation loss: 0.457[[ 0.32780477]
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[[ 0.05476638 -0.14491198  0.03861367 ..., -0.13661457  0.15876709
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  -0.24030342]
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   0.20624284]]
Progress: 7.3% ... Training loss: 0.290 ... Validation loss: 0.452[[ 0.33091299]
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[[ 0.05460509 -0.14474488  0.03907187 ..., -0.13656438  0.15825196
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  -0.24050528]
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   0.20516067]]
Progress: 7.3% ... Training loss: 0.287 ... Validation loss: 0.454[[ 0.34154222]
 [-0.28301229]
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[[ 0.05535384 -0.14537346  0.03742831 ..., -0.13674788  0.15982286
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  -0.24074957]
 [ 0.06018434 -0.0345691  -0.07605711 ...,  0.03825919  0.26540597
   0.20430506]]
Progress: 7.3% ... Training loss: 0.312 ... Validation loss: 0.481[[ 0.3256885 ]
 [-0.29795383]
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[[ 0.05449074 -0.14465413  0.03939522 ..., -0.13656611  0.15755796
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 [-0.19056633 -0.18529713 -0.12197797 ...,  0.10618902 -0.05797168
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 [ 0.06008247 -0.03445763 -0.07578182 ...,  0.03828844  0.26511004
   0.204662  ]]
Progress: 7.3% ... Training loss: 0.291 ... Validation loss: 0.448[[ 0.33279053]
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[[ 0.05457718 -0.1447659   0.03916353 ..., -0.13659491  0.15783288
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 [ 0.06042363 -0.03477399 -0.07657135 ...,  0.03820103  0.26598092
   0.20367803]]
Progress: 7.3% ... Training loss: 0.289 ... Validation loss: 0.449[[ 0.33322571]
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[[ 0.05517792 -0.14533488  0.03777081 ..., -0.13674645  0.15941311
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  -0.24001583]
 [ 0.0607092  -0.03502882 -0.07722965 ...,  0.03812992  0.26679824
   0.20301765]]
Progress: 7.3% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.34182976]
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[[ 0.05595921 -0.14602633  0.03594883 ..., -0.13694976  0.16148375
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 [-0.19068332 -0.18520433 -0.12170317 ...,  0.10621021 -0.05843593
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  -0.23999199]
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   0.2040378 ]]
Progress: 7.3% ... Training loss: 0.306 ... Validation loss: 0.481[[ 0.32567843]
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[[ 0.05484027 -0.14509679  0.0385901  ..., -0.13670181  0.15900546
  -0.18441842]
 [ 0.0375618   0.049803    0.12118911 ..., -0.24359778 -0.04731961
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 [-0.19117924 -0.18479355 -0.12060273 ...,  0.10632257 -0.05965951
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   0.2046227 ]]
Progress: 7.3% ... Training loss: 0.295 ... Validation loss: 0.455[[ 0.32875079]
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[[ 0.05494192 -0.14511354  0.03853778 ..., -0.13670549  0.15929141
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 [ 0.05978486 -0.03416784 -0.0749076  ...,  0.03837932  0.26522424
   0.20538095]]
Progress: 7.3% ... Training loss: 0.288 ... Validation loss: 0.449[[ 0.33430796]
 [-0.29225608]
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 [ 1.25947885]
 [ 0.42309018]
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[[ 0.05506716 -0.14521284  0.03825524 ..., -0.13674676  0.15947227
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 [ 0.06029611 -0.03464464 -0.07616662 ...,  0.03824377  0.26651925
   0.20414867]]
Progress: 7.3% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.33357392]
 [-0.29394782]
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[[ 0.05458978 -0.14480904  0.03937999 ..., -0.13664083  0.15823918
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  -0.24026674]
 [ 0.06057604 -0.03489888 -0.07685301 ...,  0.03817217  0.26727502
   0.20347801]]
Progress: 7.3% ... Training loss: 0.287 ... Validation loss: 0.450[[ 0.32942021]
 [-0.29801374]
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[[ 0.0541593  -0.14441366  0.04041777 ..., -0.13653148  0.15714396
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  -0.239241  ]
 [ 0.06091429 -0.03517856 -0.07761145 ...,  0.03809924  0.26816763
   0.20276186]]
Progress: 7.3% ... Training loss: 0.288 ... Validation loss: 0.449[[ 0.33630547]
 [-0.2903564 ]
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[[ 0.05416365 -0.14441361  0.04047704 ..., -0.13653119  0.15698695
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 [ 0.06120497 -0.03542887 -0.0782963  ...,  0.03802222  0.26895398
   0.20203537]]
Progress: 7.3% ... Training loss: 0.290 ... Validation loss: 0.462[[ 0.32663766]
 [-0.29835753]
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 [ 1.25203934]
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[[ 0.05352012 -0.14381513  0.04213076 ..., -0.13637552  0.15551489
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 [ 0.06087175 -0.03512839 -0.07755792 ...,  0.03810996  0.26834708
   0.20283962]]
Progress: 7.4% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.3306587 ]
 [-0.29512691]
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[[ 0.0541477  -0.14439226  0.04065995 ..., -0.13654575  0.15715445
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 [ 0.06075614 -0.03501713 -0.07725018 ...,  0.03813718  0.26806522
   0.20315721]]
Progress: 7.4% ... Training loss: 0.287 ... Validation loss: 0.453[[ 0.32959816]
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[[ 0.05424752 -0.14447327  0.04051105 ..., -0.13656358  0.15743067
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  -0.24055823]
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   0.20318639]]
Progress: 7.4% ... Training loss: 0.287 ... Validation loss: 0.451[[ 0.33562778]
 [-0.29068753]
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[[ 0.05484812 -0.14498417  0.0391468  ..., -0.13668181  0.15863351
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 [ 0.06083567 -0.03501983 -0.07744218 ...,  0.03813739  0.26833521
   0.20299187]]
Progress: 7.4% ... Training loss: 0.294 ... Validation loss: 0.459[[ 0.31905544]
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[[ 0.05397101 -0.14418411  0.04123757 ..., -0.13646202  0.15635002
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   0.20456192]]
Progress: 7.4% ... Training loss: 0.304 ... Validation loss: 0.464[[ 0.33416866]
 [-0.29096505]
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[[ 0.055394   -0.14557499  0.03785786 ..., -0.13686866  0.15989527
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 [-0.19206998 -0.18402938 -0.1184521  ...,  0.10652245 -0.06185136
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  -0.24218488]
 [ 0.06054885 -0.03477229 -0.0767956  ...,  0.03819324  0.26779518
   0.20367377]]
Progress: 7.4% ... Training loss: 0.293 ... Validation loss: 0.462[[ 0.32834857]
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[[ 0.05491894 -0.14510916  0.03913304 ..., -0.13673305  0.15875269
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 [ 0.05978982 -0.03407227 -0.07502258 ...,  0.03838978  0.26628168
   0.20550491]]
Progress: 7.4% ... Training loss: 0.287 ... Validation loss: 0.455[[ 0.33461267]
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[[ 0.05583609 -0.14597105  0.0369408  ..., -0.13698194  0.1609837
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 [-0.19155371 -0.18449083 -0.11962186 ...,  0.10638916 -0.06084993
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  -0.24160258]
 [ 0.0606556  -0.0348794  -0.0771365  ...,  0.03815828  0.26863492
   0.2033092 ]]
Progress: 7.4% ... Training loss: 0.294 ... Validation loss: 0.464[[ 0.31339966]
 [-0.30956853]
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[[ 0.05411894 -0.14443751  0.04107157 ..., -0.136553    0.15716207
  -0.1828957 ]
 [ 0.03797693  0.04941118  0.12008807 ..., -0.2437246  -0.04602426
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 [-0.19204297 -0.18406352 -0.11854273 ...,  0.10650695 -0.06208165
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  -0.2411165 ]
 [ 0.06033528 -0.03461147 -0.07645768 ...,  0.03824457  0.26819546
   0.20406415]]
Progress: 7.4% ... Training loss: 0.323 ... Validation loss: 0.485[[ 0.3428621 ]
 [-0.28448369]
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[[ 0.05598551 -0.14625701  0.03644695 ..., -0.13714842  0.16199868
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 [ 0.06082247 -0.03509622 -0.07768334 ...,  0.03809505  0.26943581
   0.20277606]]
Progress: 7.4% ... Training loss: 0.327 ... Validation loss: 0.486[[ 0.32319861]
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[[ 0.05452684 -0.14503353  0.03973946 ..., -0.13684078  0.15819192
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   0.20399822]]
Progress: 7.4% ... Training loss: 0.293 ... Validation loss: 0.454[[ 0.33897414]
 [-0.28960782]
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 [ 1.27521692]
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[[ 0.05613897 -0.14655189  0.03595129 ..., -0.13727362  0.16189336
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 [ 0.06062631 -0.03495611 -0.07725718 ...,  0.03812306  0.26918795
   0.20311648]]
Progress: 7.4% ... Training loss: 0.308 ... Validation loss: 0.461[[ 0.31804656]
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[[ 0.05444536 -0.14509751  0.0399079  ..., -0.13689019  0.15802236
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  -0.23921159]
 [ 0.06023582 -0.03461274 -0.07631848 ...,  0.03821737  0.26837959
   0.20399384]]
Progress: 7.4% ... Training loss: 0.308 ... Validation loss: 0.469[[ 0.33096809]
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[[ 0.05512433 -0.14577618  0.03843179 ..., -0.13709375  0.15946212
  -0.1862222 ]
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  -0.24045211]
 [ 0.06066823 -0.03504049 -0.07737865 ...,  0.03808487  0.26944278
   0.20291314]]
Progress: 7.4% ... Training loss: 0.287 ... Validation loss: 0.450[[ 0.32368637]
 [-0.30032956]
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[[ 0.05433747 -0.14506414  0.04030446 ..., -0.13690118  0.15772267
  -0.18446678]
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  -0.23946311]
 [ 0.0595985  -0.0340289  -0.07474492 ...,  0.03836839  0.26721474
   0.20556685]]
Progress: 7.4% ... Training loss: 0.294 ... Validation loss: 0.458[[ 0.32954182]
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[[ 0.05467776 -0.14538821  0.03954526 ..., -0.1370083   0.15862723
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 [ 0.05941218 -0.03384179 -0.07428088 ...,  0.03841669  0.26687889
   0.20607845]]
Progress: 7.5% ... Training loss: 0.286 ... Validation loss: 0.451[[ 0.33159101]
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[[ 0.05481639 -0.14540192  0.03946525 ..., -0.13702514  0.15904671
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   0.20531802]]
Progress: 7.5% ... Training loss: 0.288 ... Validation loss: 0.451[[ 0.33337421]
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[[ 0.05517328 -0.14571015  0.03864894 ..., -0.13712193  0.15990695
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   0.20544295]]
Progress: 7.5% ... Training loss: 0.291 ... Validation loss: 0.452[[ 0.32757505]
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[[ 0.05498365 -0.14554383  0.03915552 ..., -0.1370651   0.15943578
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   0.20662064]]
Progress: 7.5% ... Training loss: 0.287 ... Validation loss: 0.445[[ 0.32416388]
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[[ 0.05490586 -0.14550731  0.03932497 ..., -0.13706541  0.15923871
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  -0.24003336]
 [ 0.05917826 -0.03356189 -0.07371859 ...,  0.03848181  0.26669164
   0.20682781]]
Progress: 7.5% ... Training loss: 0.288 ... Validation loss: 0.450[[ 0.33367735]
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[[ 0.05519836 -0.14576092  0.03874736 ..., -0.13715027  0.16022367
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 [-0.19227298 -0.1839435  -0.11802661 ...,  0.10646257 -0.06298014
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 [ 0.05918189 -0.03356647 -0.07373206 ...,  0.03848233  0.26681132
   0.2068139 ]]
Progress: 7.5% ... Training loss: 0.292 ... Validation loss: 0.453[[ 0.31992845]
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[[ 0.05445407 -0.1450926   0.04058883 ..., -0.13697241  0.15822112
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 [-0.19237681 -0.183863   -0.11779728 ...,  0.10649121 -0.0634847
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 [ 0.05860063 -0.03303654 -0.07232988 ...,  0.03862553  0.26559879
   0.2082456 ]]
Progress: 7.5% ... Training loss: 0.297 ... Validation loss: 0.462[[ 0.34148043]
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[[ 0.0564429  -0.14698283  0.03572799 ..., -0.13753602  0.1630536
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 [-0.19188381 -0.18433165 -0.11894585 ...,  0.10635323 -0.06230876
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 [ 0.05879654 -0.03321493 -0.07277803 ...,  0.03857163  0.26605793
   0.20780045]]
Progress: 7.5% ... Training loss: 0.321 ... Validation loss: 0.480[[ 0.32002662]
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[[ 0.05467128 -0.14548303  0.03980181 ..., -0.13716651  0.1588065
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   0.20879204]]
Progress: 7.5% ... Training loss: 0.298 ... Validation loss: 0.466[[ 0.32814668]
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[[ 0.05474147 -0.14551152  0.03975056 ..., -0.13717138  0.15898365
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 [-0.1922532  -0.18404585 -0.1181604  ...,  0.10642919 -0.06317825
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 [ 0.05862302 -0.03307943 -0.07238076 ...,  0.03860783  0.26595401
   0.20830242]]
Progress: 7.5% ... Training loss: 0.287 ... Validation loss: 0.451[[ 0.33154697]
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[[ 0.05457165 -0.14538851  0.04013205 ..., -0.13713282  0.15853059
  -0.18435581]
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 [-0.19215202 -0.18413836 -0.1184065  ...,  0.10640185 -0.06297817
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   0.20748132]]
Progress: 7.5% ... Training loss: 0.288 ... Validation loss: 0.453[[ 0.32471914]
 [-0.29607136]
 [-0.78925383]
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 [ 0.41817239]
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[[ 0.05414437 -0.14500564  0.04114396 ..., -0.1370349   0.15744309
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  -0.24005467]
 [ 0.05911399 -0.03348617 -0.07351882 ...,  0.03849112  0.26727869
   0.20707635]]
Progress: 7.5% ... Training loss: 0.289 ... Validation loss: 0.458[[ 0.3310491 ]
 [-0.29125186]
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[[ 0.05439839 -0.14521238  0.04060693 ..., -0.13708836  0.15821637
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  -0.24107875]
 [ 0.05863523 -0.03301959 -0.07233    ...,  0.03862758  0.26624624
   0.20829682]]
Progress: 7.5% ... Training loss: 0.287 ... Validation loss: 0.454[[ 0.32122183]
 [-0.29993734]
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[[ 0.05410196 -0.14493342  0.04140636 ..., -0.13701396  0.15772289
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 [-0.19256164 -0.1837988  -0.11749408 ...,  0.10648687 -0.0639522
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  -0.24073042]
 [ 0.05825062 -0.03267402 -0.07139692 ...,  0.03872484  0.26541245
   0.20916075]]
Progress: 7.5% ... Training loss: 0.294 ... Validation loss: 0.464[[ 0.34461041]
 [-0.28261784]
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[[ 0.0562715  -0.14701021  0.03611711 ..., -0.13762082  0.16327513
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   0.20749663]]
Progress: 7.5% ... Training loss: 0.332 ... Validation loss: 0.492[[ 0.31519372]
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[[ 0.05351181 -0.14472549  0.04225177 ..., -0.13706163  0.15661454
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 [-0.19268771 -0.18373778 -0.11727334 ...,  0.10648393 -0.064226   -0.0311596 ]
 [-0.27723021 -0.22463161 -0.0513016  ..., -0.11807755 -0.00985796
  -0.24029324]
 [ 0.05887012 -0.03325132 -0.07288056 ...,  0.03855849  0.26712     0.20751283]]
Progress: 7.6% ... Training loss: 0.322 ... Validation loss: 0.490[[ 0.34281981]
 [-0.28462074]
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[[ 0.05580156 -0.14700345  0.03642364 ..., -0.13774094  0.16229833
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 [ 0.05939653 -0.03376846 -0.07427953 ...,  0.03839481  0.26846132
   0.20609307]]
Progress: 7.6% ... Training loss: 0.319 ... Validation loss: 0.493[[ 0.32660001]
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[[ 0.05477178 -0.14616139  0.03874444 ..., -0.13752555  0.159911
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   0.20525583]]
Progress: 7.6% ... Training loss: 0.289 ... Validation loss: 0.457[[ 0.32547013]
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[[ 0.05432409 -0.14573938  0.03983297 ..., -0.13739677  0.15876431
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 [ 0.0595043  -0.03381552 -0.07451733 ...,  0.03838218  0.268749
   0.20576489]]
Progress: 7.6% ... Training loss: 0.290 ... Validation loss: 0.458[[ 0.32870695]
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[[ 0.0544611  -0.14592694  0.03939832 ..., -0.13746618  0.15925307
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 [ 0.059693   -0.03399537 -0.07498697 ...,  0.038329    0.26930775
   0.20525626]]
Progress: 7.6% ... Training loss: 0.287 ... Validation loss: 0.457[[ 0.32383611]
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[[ 0.05502113 -0.14640519  0.0381661  ..., -0.13760818  0.16041515
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 [-0.19247092 -0.18401444 -0.11797925 ...,  0.10636517 -0.06371051
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  -0.24197094]
 [ 0.05949993 -0.03380116 -0.07451445 ...,  0.03838297  0.26887107
   0.20571401]]
Progress: 7.6% ... Training loss: 0.292 ... Validation loss: 0.461[[ 0.33004043]
 [-0.29827037]
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[[ 0.05586029 -0.14720395  0.03610229 ..., -0.13783453  0.1626647
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 [-0.1922024  -0.18426487 -0.11862978 ...,  0.10629397 -0.06300641
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  -0.24116781]
 [ 0.05997134 -0.03425881 -0.075723   ...,  0.03825761  0.27019161
   0.20452194]]
Progress: 7.6% ... Training loss: 0.286 ... Validation loss: 0.453[[ 0.33418258]
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[[ 0.0563231  -0.14760962  0.03497057 ..., -0.13794363  0.16364085
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 [ 0.03767544  0.04961296  0.1204034  ..., -0.24370507 -0.04633833
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 [-0.19228944 -0.18418444 -0.11850423 ...,  0.10631717 -0.06329649
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 [ 0.06049212 -0.03473365 -0.07701734 ...,  0.03812686  0.27152672
   0.2032935 ]]
Progress: 7.6% ... Training loss: 0.290 ... Validation loss: 0.458[[ 0.33160745]
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[[ 0.05544982 -0.14685442  0.03697059 ..., -0.13773348  0.16143631
  -0.18743041]
 [ 0.03789816  0.0494235   0.1198839  ..., -0.24375742 -0.04578086
   0.12585295]
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 [-0.1925613  -0.18394586 -0.11786969 ...,  0.10638385 -0.06399601
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  -0.24100715]
 [ 0.06065386 -0.03487376 -0.0774438  ...,  0.03807988  0.27201774
   0.20287655]]
Progress: 7.6% ... Training loss: 0.286 ... Validation loss: 0.456[[ 0.32964771]
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[[ 0.0544656  -0.14595998  0.03927267 ..., -0.13748956  0.15897995
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   0.20271688]]
Progress: 7.6% ... Training loss: 0.286 ... Validation loss: 0.455[[ 0.32897094]
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[[ 0.05448737 -0.14598183  0.0391761  ..., -0.13748856  0.15902659
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   0.2024031 ]]
Progress: 7.6% ... Training loss: 0.286 ... Validation loss: 0.454[[ 0.32695733]
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[[ 0.05423296 -0.14580322  0.03982395 ..., -0.13742994  0.15846452
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   0.20151953]]
Progress: 7.6% ... Training loss: 0.288 ... Validation loss: 0.457[[ 0.33772209]
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[[ 0.0544297  -0.14598845  0.03941197 ..., -0.13746683  0.15916406
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  -0.24049235]
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   0.20128923]]
Progress: 7.6% ... Training loss: 0.293 ... Validation loss: 0.464[[ 0.31930879]
 [-0.30606929]
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[[ 0.05354487 -0.14519373  0.04155648 ..., -0.13725479  0.15696123
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  -0.2403621 ]
 [ 0.06045624 -0.0346952  -0.07696197 ...,  0.03812337  0.27240373
   0.20298408]]
Progress: 7.6% ... Training loss: 0.310 ... Validation loss: 0.473[[ 0.34799188]
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[[ 0.05577102 -0.14736496  0.03604278 ..., -0.13791377  0.1625783
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   0.20061187]]
Progress: 7.6% ... Training loss: 0.341 ... Validation loss: 0.506[[ 0.31546539]
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[[ 0.05337093 -0.14537455  0.04139339 ..., -0.1374244   0.15698183
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 [ 0.0598284  -0.03430207 -0.07587195 ...,  0.03817446  0.27154287
   0.20423438]]
Progress: 7.7% ... Training loss: 0.326 ... Validation loss: 0.489[[ 0.33820638]
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   0.20393807]]
Progress: 7.7% ... Training loss: 0.292 ... Validation loss: 0.467[[ 0.31198688]
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[[ 0.05309898 -0.145336    0.04190545 ..., -0.13746161  0.15667714
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   0.20508233]]
Progress: 7.7% ... Training loss: 0.353 ... Validation loss: 0.516[[ 0.33708682]
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[[ 0.05496495 -0.14720022  0.03733644 ..., -0.13806084  0.16131356
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 [ 0.05960468 -0.03411685 -0.0754157  ...,  0.03822145  0.27129496
   0.20468145]]
Progress: 7.7% ... Training loss: 0.296 ... Validation loss: 0.472[[ 0.31596209]
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[[ 0.05333506 -0.14577359  0.04114605 ..., -0.13766827  0.15739131
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   0.20467745]]
Progress: 7.7% ... Training loss: 0.317 ... Validation loss: 0.487[[ 0.33094741]
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[[ 0.05415867 -0.14658055  0.03900369 ..., -0.1379051   0.159671
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  -0.24006926]
 [ 0.05958449 -0.03409118 -0.0753998  ...,  0.03823376  0.27159297
   0.20464422]]
Progress: 7.7% ... Training loss: 0.287 ... Validation loss: 0.459[[ 0.32917906]
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[[ 0.05454539 -0.14693574  0.03824932 ..., -0.13801925  0.16066531
  -0.18679402]
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   0.20475958]]
Progress: 7.7% ... Training loss: 0.286 ... Validation loss: 0.456[[ 0.32798869]
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[[ 0.05507985 -0.14741661  0.03695886 ..., -0.13815361  0.16193775
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 [ 0.05991328 -0.03437756 -0.07622477 ...,  0.03814661  0.27262438
   0.20377081]]
Progress: 7.7% ... Training loss: 0.285 ... Validation loss: 0.453[[ 0.32903803]
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[[ 0.05542982 -0.14772168  0.0362156  ..., -0.1382475   0.16286278
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 [-0.19180402 -0.18492842 -0.12000723 ...,  0.10600934 -0.06219791
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   0.2043154 ]]
Progress: 7.7% ... Training loss: 0.285 ... Validation loss: 0.452[[ 0.32723418]
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[[ 0.0555399  -0.14782074  0.03610416 ..., -0.13825058  0.16284019
  -0.1891926 ]
 [ 0.03772809  0.04955716  0.12016165 ..., -0.24371779 -0.04608309
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  -0.24112808]
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   0.20457955]]
Progress: 7.7% ... Training loss: 0.285 ... Validation loss: 0.454[[ 0.32591528]
 [-0.29534851]
 [-0.78428046]
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 [ 1.27305365]
 [ 0.41658192]
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[[ 0.05585951 -0.148081    0.03549631 ..., -0.13833346  0.16336434
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   0.20421197]]
Progress: 7.7% ... Training loss: 0.286 ... Validation loss: 0.455[[ 0.33151606]
 [-0.29080819]
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[[ 0.05588387 -0.14809666  0.03559559 ..., -0.13832034  0.1634382
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  -0.24082934]
 [ 0.05956318 -0.03401807 -0.07535554 ...,  0.03826179  0.27214525
   0.20455843]]
Progress: 7.7% ... Training loss: 0.288 ... Validation loss: 0.458[[ 0.31934103]
 [-0.30099646]
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 [ 1.26749223]
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[[ 0.05466063 -0.14700976  0.03852531 ..., -0.13801301  0.16037234
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  -0.24023691]
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   0.20630304]]
Progress: 7.7% ... Training loss: 0.299 ... Validation loss: 0.470[[ 0.33632551]
 [-0.28499132]
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 [ 1.28383188]
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[[ 0.056285   -0.14847811  0.03463373 ..., -0.13846866  0.16434135
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 [ 0.05913886 -0.03364056 -0.07438517 ...,  0.03834906  0.27132555
   0.20554547]]
Progress: 7.7% ... Training loss: 0.303 ... Validation loss: 0.468[[ 0.31268749]
 [-0.30587631]
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[[ 0.05373072 -0.14628771  0.04057807 ..., -0.13789745  0.15808944
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   0.20708884]]
Progress: 7.7% ... Training loss: 0.323 ... Validation loss: 0.492[[ 0.32950217]
 [-0.28958479]
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[[ 0.05442819 -0.14696437  0.03885389 ..., -0.1381228   0.16007539
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 [ 0.05879117 -0.0333563  -0.07359325 ...,  0.03839962  0.27078888
   0.2061582 ]]
Progress: 7.8% ... Training loss: 0.287 ... Validation loss: 0.452[[ 0.32814272]
 [-0.29241267]
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 [ 1.27919999]
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[[ 0.05453821 -0.14708575  0.038613   ..., -0.13815259  0.16043627
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 [ 0.05854972 -0.03310979 -0.07301768 ...,  0.03845895  0.27036535
   0.20686008]]
Progress: 7.8% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.3238949 ]
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[[ 0.05392336 -0.14651686  0.04017695 ..., -0.13799965  0.15896265
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 [ 0.05877674 -0.0333311  -0.07358725 ...,  0.03839797  0.27094226
   0.20627604]]
Progress: 7.8% ... Training loss: 0.288 ... Validation loss: 0.454[[ 0.33493711]
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[[ 0.05445369 -0.14700516  0.03897907 ..., -0.13813867  0.16018173
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 [ 0.0591048  -0.03363336 -0.0743478  ...,  0.03831221  0.27183771
   0.20546735]]
Progress: 7.8% ... Training loss: 0.291 ... Validation loss: 0.459[[ 0.31916879]
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[[ 0.05343941 -0.14603245  0.0414036  ..., -0.13789747  0.15776958
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 [ 0.03800943  0.04927349  0.11934756 ..., -0.24382135 -0.04522239
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 [-0.19081386 -0.18592109 -0.12211811 ...,  0.10568702 -0.05983185
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 [ 0.05834361 -0.03291595 -0.07254458 ...,  0.03850179  0.27019522
   0.207252  ]]
Progress: 7.8% ... Training loss: 0.300 ... Validation loss: 0.467[[ 0.33810811]
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[[ 0.05460762 -0.14711791  0.03851545 ..., -0.13822224  0.16080819
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  -0.24187987]
 [ 0.05851275 -0.03307603 -0.0730174  ...,  0.03845933  0.27079761
   0.20683647]]
Progress: 7.8% ... Training loss: 0.299 ... Validation loss: 0.470[[ 0.33454157]
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[[ 0.05476518 -0.14726037  0.03806444 ..., -0.13826547  0.16134906
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 [-0.19072762 -0.18599309 -0.12223138 ...,  0.10564802 -0.05971223
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 [ 0.05943183 -0.03388795 -0.07524614 ...,  0.0382527   0.27315025
   0.20462592]]
Progress: 7.8% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.33389547]
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[[ 0.05414287 -0.1467084   0.03958143 ..., -0.13812697  0.15976927
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 [-0.19100851 -0.18574927 -0.12159259 ...,  0.10571185 -0.06042845
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  -0.24118344]
 [ 0.05942138 -0.03384889 -0.07520217 ...,  0.03826334  0.27313306
   0.20467025]]
Progress: 7.8% ... Training loss: 0.288 ... Validation loss: 0.450[[ 0.32721543]
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[[ 0.05408326 -0.1467024   0.03962041 ..., -0.13812802  0.15978809
  -0.1861887 ]
 [ 0.03827375  0.04905088  0.11871931 ..., -0.24387978 -0.04450437
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 [ 0.05864954 -0.0331555  -0.07340152 ...,  0.03844069  0.27146257
   0.20652798]]
Progress: 7.8% ... Training loss: 0.288 ... Validation loss: 0.451[[ 0.33568843]
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[[ 0.05376946 -0.14640579  0.04051267 ..., -0.13804272  0.15883175
  -0.18551911]
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   0.20773965]]
Progress: 7.8% ... Training loss: 0.289 ... Validation loss: 0.454[[ 0.3204736 ]
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   0.20835112]]
Progress: 7.8% ... Training loss: 0.304 ... Validation loss: 0.469[[ 0.34054863]
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[[ 0.05438854 -0.14699519  0.03915338 ..., -0.13821487  0.16052208
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  -0.2404709 ]
 [ 0.0585648  -0.0330922  -0.07328106 ...,  0.03845219  0.27170395
   0.20683926]]
Progress: 7.8% ... Training loss: 0.301 ... Validation loss: 0.469[[ 0.32417124]
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[[ 0.05306043 -0.14584975  0.04232601 ..., -0.13793765  0.15716048
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  -0.23971939]
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   0.20605063]]
Progress: 7.8% ... Training loss: 0.293 ... Validation loss: 0.456[[ 0.3373211 ]
 [-0.29154443]
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 [ 0.05896461 -0.03341442 -0.074185   ...,  0.03837531  0.2727537
   0.20596945]]
Progress: 7.8% ... Training loss: 0.292 ... Validation loss: 0.455[[ 0.32481995]
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   0.2055858 ]]
Progress: 7.8% ... Training loss: 0.292 ... Validation loss: 0.454[[ 0.33413238]
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[[ 0.0532296  -0.14609875  0.04174586 ..., -0.13805458  0.15761685
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 [ 0.05901386 -0.03344793 -0.07429627 ...,  0.03836902  0.27308252
   0.20584568]]
Progress: 7.9% ... Training loss: 0.285 ... Validation loss: 0.446[[ 0.32280537]
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[[ 0.05177777 -0.14478788  0.04506411 ..., -0.13772065  0.1541456
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 [ 0.05873765 -0.03319276 -0.07367525 ...,  0.0384406   0.27242829
   0.20649602]]
Progress: 7.9% ... Training loss: 0.299 ... Validation loss: 0.463[[ 0.34154422]
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[[ 0.05350529 -0.14640328  0.04103175 ..., -0.13818166  0.15815125
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 [ 0.0592536  -0.03369011 -0.07497221 ...,  0.03829979  0.27368196
   0.20521661]]
Progress: 7.9% ... Training loss: 0.305 ... Validation loss: 0.460[[ 0.31574172]
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[[ 0.05115155 -0.14438661  0.04621764 ..., -0.13767624  0.15270731
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 [ 0.05851788 -0.0330461  -0.07331867 ...,  0.03845552  0.27224021
   0.20697695]]
Progress: 7.9% ... Training loss: 0.321 ... Validation loss: 0.490[[ 0.34186624]
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[[ 0.05308611 -0.14633803  0.04127454 ..., -0.13822475  0.15764435
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  -0.24022991]
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   0.2068405 ]]
Progress: 7.9% ... Training loss: 0.308 ... Validation loss: 0.468[[ 0.31846008]
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[[ 0.05144147 -0.14495099  0.04501241 ..., -0.13788912  0.15363993
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 [-0.19039364 -0.186575   -0.12343385 ...,  0.10541303 -0.05948534
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   0.20808903]]
Progress: 7.9% ... Training loss: 0.314 ... Validation loss: 0.481[[ 0.33612121]
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[[ 0.05222856 -0.14573593  0.04307737 ..., -0.13809893  0.15563528
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 [-0.19027151 -0.186694   -0.12372434 ...,  0.10538019 -0.05924724
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  -0.23951703]
 [ 0.05860574 -0.03316166 -0.07359235 ...,  0.03840772  0.27298515
   0.20660331]]
Progress: 7.9% ... Training loss: 0.288 ... Validation loss: 0.456[[ 0.32289784]
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[[ 0.05146458 -0.14505654  0.0448415  ..., -0.13792353  0.15392041
  -0.18145196]
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 [-0.19073899 -0.1862906  -0.12270451 ...,  0.10547995 -0.06035479
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  -0.23915654]
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   0.20670146]]
Progress: 7.9% ... Training loss: 0.295 ... Validation loss: 0.468[[ 0.33932416]
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[[ 0.05237523 -0.14590539  0.04281334 ..., -0.13814858  0.15587466
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   0.20562549]]
Progress: 7.9% ... Training loss: 0.298 ... Validation loss: 0.468[[ 0.317734  ]
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   0.20644705]]
Progress: 7.9% ... Training loss: 0.315 ... Validation loss: 0.492[[ 0.33136065]
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[[ 0.05163339 -0.14534814  0.04452822 ..., -0.13803453  0.15400685
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   0.20511685]]
Progress: 7.9% ... Training loss: 0.287 ... Validation loss: 0.459[[ 0.32710604]
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[[ 0.05143429 -0.14521236  0.0451288  ..., -0.13799866  0.15367232
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   0.20603524]]
Progress: 7.9% ... Training loss: 0.287 ... Validation loss: 0.459[[ 0.32564502]
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[[ 0.05086585 -0.14469162  0.04658947 ..., -0.13784817  0.15222998
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   0.20749859]]
Progress: 7.9% ... Training loss: 0.290 ... Validation loss: 0.464[[ 0.34578796]
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   0.20538732]]
Progress: 7.9% ... Training loss: 0.324 ... Validation loss: 0.493[[ 0.32359399]
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[[ 0.0509613  -0.14496131  0.04622634 ..., -0.13801147  0.15254173
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   0.20666403]]
Progress: 7.9% ... Training loss: 0.296 ... Validation loss: 0.466[[ 0.33260048]
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   0.20697545]]
Progress: 8.0% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.32862364]
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   0.20726372]]
Progress: 8.0% ... Training loss: 0.286 ... Validation loss: 0.453[[ 0.32744147]
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[[ 0.0514848  -0.14546844  0.04517764 ..., -0.1381865   0.15406487
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   0.20687633]]
Progress: 8.0% ... Training loss: 0.288 ... Validation loss: 0.457[[ 0.33462964]
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[[ 0.05193612 -0.14582822  0.04432317 ..., -0.13829899  0.1551601
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   0.20459953]]
Progress: 8.0% ... Training loss: 0.286 ... Validation loss: 0.451[[ 0.33288903]
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[[ 0.05190352 -0.14576216  0.04443563 ..., -0.1382645   0.15508708
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   0.20666036]]
Progress: 8.0% ... Training loss: 0.285 ... Validation loss: 0.448[[ 0.32628164]
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[[ 0.05185704 -0.14572834  0.04453062 ..., -0.13825353  0.15491135
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 [ 0.0583644  -0.03298623 -0.0732935  ...,  0.03840324  0.27422788
   0.20667454]]
Progress: 8.0% ... Training loss: 0.288 ... Validation loss: 0.454[[ 0.32664211]
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[[ 0.05103249 -0.14496407  0.04646103 ..., -0.13802826  0.15330838
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 ..., 
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   0.20768382]]
Progress: 8.0% ... Training loss: 0.288 ... Validation loss: 0.454[[ 0.33694141]
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[[ 0.05204895 -0.14588546  0.04405489 ..., -0.13827995  0.15566623
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   0.20687228]]
Progress: 8.0% ... Training loss: 0.291 ... Validation loss: 0.451[[ 0.3331297 ]
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[[ 0.05227737 -0.14604931  0.04373426 ..., -0.13831155  0.15594055
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   0.20787742]]
Progress: 8.0% ... Training loss: 0.287 ... Validation loss: 0.447[[ 0.33734459]
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 [ 0.42868536]
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[[ 0.0527241  -0.14648133  0.04259072 ..., -0.13841624  0.15724394
  -0.18517286]
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   0.20717098]]
Progress: 8.0% ... Training loss: 0.292 ... Validation loss: 0.446[[ 0.32676031]
 [-0.29965162]
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 [ 0.41824076]
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[[ 0.05204819 -0.1459103   0.04413425 ..., -0.13827716  0.15574508
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  -0.23801336]
 [ 0.05751569 -0.03219929 -0.07138185 ...,  0.03861143  0.27285946
   0.20847545]]
Progress: 8.0% ... Training loss: 0.289 ... Validation loss: 0.452[[ 0.34939063]
 [-0.28317723]
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[[ 0.05372913 -0.14751986  0.04003131 ..., -0.13874033  0.15987195
  -0.18734806]
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   0.20735329]]
Progress: 8.0% ... Training loss: 0.329 ... Validation loss: 0.487[[ 0.33002013]
 [-0.29992573]
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[[ 0.05247154 -0.14643996  0.04294552 ..., -0.13848876  0.15689227
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   0.20794714]]
Progress: 8.0% ... Training loss: 0.286 ... Validation loss: 0.448[[ 0.3362618 ]
 [-0.29411595]
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 [ 1.30249085]
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[[ 0.05281898 -0.14673627  0.04220415 ..., -0.13856895  0.15771005
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  -0.23947404]
 [ 0.0577349  -0.03236902 -0.0721067  ...,  0.03855354  0.27401718
   0.20793799]]
Progress: 8.0% ... Training loss: 0.285 ... Validation loss: 0.449[[ 0.34127603]
 [-0.28997509]
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[[ 0.05333721 -0.14716986  0.04114911 ..., -0.13868698  0.15881937
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 [ 0.05778452 -0.03240632 -0.07227207 ...,  0.03853183  0.27422249
   0.20769912]]
Progress: 8.0% ... Training loss: 0.297 ... Validation loss: 0.456[[ 0.3339691 ]
 [-0.29595821]
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[[ 0.0527222  -0.14662538  0.04276588 ..., -0.13855198  0.15728123
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   0.20703862]]
Progress: 8.1% ... Training loss: 0.285 ... Validation loss: 0.443[[ 0.33524201]
 [-0.29320688]
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[[ 0.05227843 -0.14622794  0.04388181 ..., -0.13844054  0.15604352
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   0.20681028]]
Progress: 8.1% ... Training loss: 0.284 ... Validation loss: 0.449[[ 0.33438939]
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[[ 0.0518661  -0.14591131  0.04475433 ..., -0.13835576  0.15512326
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 [ 0.0579681  -0.03251613 -0.07267227 ...,  0.03849806  0.27496093
   0.2073517 ]]
Progress: 8.1% ... Training loss: 0.283 ... Validation loss: 0.449[[ 0.32643571]
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[[ 0.05165009 -0.14571584  0.04546897 ..., -0.13830288  0.15471965
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  -0.23846954]
 [ 0.05758949 -0.03216607 -0.0717896  ...,  0.03859918  0.27420153
   0.20817016]]
Progress: 8.1% ... Training loss: 0.294 ... Validation loss: 0.459[[ 0.33375301]
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[[ 0.05251746 -0.14651246  0.04341489 ..., -0.13853527  0.15665771
  -0.18377279]
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 [ 0.05809574 -0.0326563  -0.07307618 ...,  0.03845561  0.27543007
   0.20685406]]
Progress: 8.1% ... Training loss: 0.284 ... Validation loss: 0.453[[ 0.33270499]
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[[ 0.05269594 -0.14668463  0.04310291 ..., -0.13858459  0.15715813
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 [-0.19121651 -0.18615063 -0.1216889  ...,  0.10538009 -0.06234648
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  -0.23886919]
 [ 0.05805698 -0.03261678 -0.07298866 ...,  0.03846107  0.275435    0.2069581 ]]
Progress: 8.1% ... Training loss: 0.284 ... Validation loss: 0.452[[ 0.32864861]
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[[ 0.0519818  -0.14597403  0.04491879 ..., -0.13839757  0.15544016
  -0.18216211]
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 [-0.19129015 -0.18608672 -0.1215297  ...,  0.10539438 -0.06261618
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  -0.23957992]
 [ 0.05748713 -0.03208412 -0.07165164 ...,  0.03861343  0.27419676
   0.2083938 ]]
Progress: 8.1% ... Training loss: 0.288 ... Validation loss: 0.456[[ 0.34284051]
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[[ 0.0537044  -0.14758092  0.04085162 ..., -0.138864    0.15969526
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 [ 0.04026932  0.04717614  0.1134947  ..., -0.24442639 -0.03891139
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 [-0.19083622 -0.18649932 -0.12260789 ...,  0.10527162 -0.06162479
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   0.20840311]]
Progress: 8.1% ... Training loss: 0.303 ... Validation loss: 0.464[[ 0.32997291]
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[[ 0.0530999  -0.14705144  0.04220672 ..., -0.13872882  0.15826187
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   0.20797071]]
Progress: 8.1% ... Training loss: 0.285 ... Validation loss: 0.448[[ 0.32910721]
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[[ 0.05332786 -0.14724719  0.0417711  ..., -0.13878898  0.15869325
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 [ 0.05732459 -0.03189635 -0.07120617 ...,  0.03867268  0.27412415
   0.20873565]]
Progress: 8.1% ... Training loss: 0.286 ... Validation loss: 0.451[[ 0.32989629]
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[[ 0.05363096 -0.1474889   0.04113563 ..., -0.13888113  0.15939437
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   0.20930473]]
Progress: 8.1% ... Training loss: 0.285 ... Validation loss: 0.448[[ 0.34572908]
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[[ 0.05479994 -0.14860368  0.03846247 ..., -0.13919165  0.16206719
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   0.20883081]]
Progress: 8.1% ... Training loss: 0.308 ... Validation loss: 0.476[[ 0.32668116]
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[[ 0.0528435  -0.1468666   0.04303105 ..., -0.13873263  0.15726443
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 [ 0.05688773 -0.03148879 -0.07007395 ...,  0.0387859   0.27344459
   0.20963722]]
Progress: 8.1% ... Training loss: 0.293 ... Validation loss: 0.455[[ 0.33319521]
 [-0.29795955]
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[[ 0.05311422 -0.14715155  0.04240707 ..., -0.13880668  0.15790485
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   0.20843876]]
Progress: 8.1% ... Training loss: 0.284 ... Validation loss: 0.447[[ 0.32876614]
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[[ 0.05322324 -0.14720955  0.0423163  ..., -0.13883837  0.15824717
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   0.20938568]]
Progress: 8.1% ... Training loss: 0.288 ... Validation loss: 0.450[[ 0.33937856]
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[[ 0.05362709 -0.1475569   0.04140229 ..., -0.13893516  0.15922048
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   0.20824043]]
Progress: 8.2% ... Training loss: 0.291 ... Validation loss: 0.449[[ 0.32357469]
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[[ 0.05274305 -0.14675986  0.04354226 ..., -0.13870879  0.15695065
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   0.20852871]]
Progress: 8.2% ... Training loss: 0.302 ... Validation loss: 0.462[[ 0.33924007]
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 [ 0.05800524 -0.03253835 -0.07298679 ...,  0.03844708  0.27702128
   0.2066579 ]]
Progress: 8.2% ... Training loss: 0.288 ... Validation loss: 0.456[[ 0.33422055]
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[[ 0.05334336 -0.14732882  0.04228811 ..., -0.13890604  0.15849448
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 [ 0.0577289  -0.03229764 -0.07235646 ...,  0.0385178   0.2764333   0.207282  ]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.449[[ 0.32676195]
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[[ 0.05336408 -0.14733902  0.04237758 ..., -0.13890938  0.15841174
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   0.20708651]]
Progress: 8.2% ... Training loss: 0.295 ... Validation loss: 0.459[[ 0.33398239]
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[[ 0.0535169  -0.14747717  0.04208039 ..., -0.13896603  0.15895139
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   0.20580034]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.451[[ 0.32992386]
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[[ 0.05365926 -0.14758339  0.04189385 ..., -0.13900873  0.15940933
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   0.20572579]]
Progress: 8.2% ... Training loss: 0.286 ... Validation loss: 0.452[[ 0.33251253]
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[[ 0.05357562 -0.14749157  0.04207569 ..., -0.13898098  0.15904525
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   0.20532541]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.449[[ 0.33583282]
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[[ 0.05451415 -0.14830939  0.03995407 ..., -0.13920783  0.16141731
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   0.20522504]]
Progress: 8.2% ... Training loss: 0.284 ... Validation loss: 0.447[[ 0.33515431]
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   0.20524195]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.446[[ 0.33325249]
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[[ 0.05442116 -0.14826914  0.04037367 ..., -0.13918161  0.16149065
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  -0.24013582]
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   0.20583697]]
Progress: 8.2% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.34819646]
 [-0.28662487]
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[[ 0.05508655 -0.14885078  0.03886353 ..., -0.13934605  0.16289969
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   0.20443398]]
Progress: 8.2% ... Training loss: 0.306 ... Validation loss: 0.479[[ 0.33342622]
 [-0.29976694]
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[[ 0.05399911 -0.1479547   0.04129964 ..., -0.13911357  0.16035276
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   0.20527108]]
Progress: 8.2% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.33704073]
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   0.20575215]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.445[[ 0.33485866]
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[[ 0.05405934 -0.14789206  0.04135201 ..., -0.13911626  0.16047611
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   0.20612635]]
Progress: 8.2% ... Training loss: 0.283 ... Validation loss: 0.446[[ 0.3300272 ]
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[[ 0.05366373 -0.14750293  0.0424078  ..., -0.13900211  0.15957752
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 [ 0.05828628 -0.03271055 -0.07381716 ...,  0.03834434  0.27924051
   0.20568269]]
Progress: 8.3% ... Training loss: 0.286 ... Validation loss: 0.451[[ 0.33742416]
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[[ 0.0545239  -0.14825535  0.04049732 ..., -0.13923391  0.16167979
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 [ 0.05827651 -0.03266024 -0.07378116 ...,  0.03836657  0.2792603
   0.20573726]]
Progress: 8.3% ... Training loss: 0.285 ... Validation loss: 0.446[[ 0.33220439]
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[[ 0.05437025 -0.14815674  0.04080422 ..., -0.13921289  0.16138496
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 [ 0.05849754 -0.03286931 -0.07435813 ...,  0.03830677  0.27984703
   0.20511715]]
Progress: 8.3% ... Training loss: 0.284 ... Validation loss: 0.449[[ 0.33624183]
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[[ 0.05454653 -0.14832813  0.04040207 ..., -0.13927357  0.16195729
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 [ 0.05840614 -0.03277634 -0.0740731  ...,  0.03833541  0.27994288
   0.20528091]]
Progress: 8.3% ... Training loss: 0.282 ... Validation loss: 0.448[[ 0.33576777]
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[[ 0.05507846 -0.14881201  0.03930266 ..., -0.13941564  0.16305589
  -0.19022403]
 [ 0.04037213  0.04708921  0.1130167  ..., -0.2444551  -0.03848041
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 [-0.19013967 -0.18722078 -0.1240147  ...,  0.10499426 -0.06065222
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  -0.24041183]
 [ 0.05836243 -0.03270639 -0.0739655  ...,  0.03835337  0.27998779
   0.20536576]]
Progress: 8.3% ... Training loss: 0.283 ... Validation loss: 0.445[[ 0.33812203]
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[[ 0.05503059 -0.14878701  0.03942147 ..., -0.13940854  0.16301569
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 [ 0.05836573 -0.03270807 -0.07394852 ...,  0.03835655  0.28011395
   0.20536205]]
Progress: 8.3% ... Training loss: 0.284 ... Validation loss: 0.446[[ 0.33912961]
 [-0.29426721]
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[[ 0.0552535  -0.14894566  0.03910801 ..., -0.13946302  0.16348971
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 [ 0.04036457  0.04709518  0.11304278 ..., -0.24445299 -0.03850273
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  -0.24039573]
 [ 0.05845456 -0.03276938 -0.07412431 ...,  0.0383403   0.2805375
   0.20520233]]
Progress: 8.3% ... Training loss: 0.285 ... Validation loss: 0.448[[ 0.33369359]
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[[ 0.05510089 -0.14880551  0.03948992 ..., -0.13941485  0.16310438
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   0.20546091]]
Progress: 8.3% ... Training loss: 0.283 ... Validation loss: 0.448[[ 0.32270073]
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[[ 0.05455026 -0.14829167  0.0408315  ..., -0.13925332  0.16183587
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   0.20632949]]
Progress: 8.3% ... Training loss: 0.310 ... Validation loss: 0.478[[ 0.34340674]
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[[ 0.05616985 -0.1498164   0.03725165 ..., -0.13973416  0.16569406
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 [ 0.05847624 -0.03279254 -0.07436522 ...,  0.03832669  0.28124256
   0.20512627]]
Progress: 8.3% ... Training loss: 0.295 ... Validation loss: 0.460[[ 0.33667389]
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[[ 0.05598145 -0.14963184  0.0377923  ..., -0.13968455  0.16512771
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 [ 0.0579203  -0.03229816 -0.0730403  ...,  0.03846743  0.28003878
   0.20649918]]
Progress: 8.3% ... Training loss: 0.282 ... Validation loss: 0.449[[ 0.34077793]
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[[ 0.05701968 -0.15053154  0.03544744 ..., -0.13995113  0.16763932
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   0.20560063]]
Progress: 8.3% ... Training loss: 0.287 ... Validation loss: 0.455[[ 0.33133955]
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[[ 0.05725031 -0.15076446  0.03488697 ..., -0.14000732  0.16831112
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   0.20558081]]
Progress: 8.3% ... Training loss: 0.285 ... Validation loss: 0.450[[ 0.35110686]
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[[ 0.05908279 -0.15239971  0.03073994 ..., -0.14049001  0.17288186
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   0.20320617]]
Progress: 8.3% ... Training loss: 0.333 ... Validation loss: 0.496[[ 0.33018704]
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[[ 0.05697215 -0.15065888  0.03554884 ..., -0.14003773  0.16783316
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   0.20549473]]
Progress: 8.3% ... Training loss: 0.286 ... Validation loss: 0.446[[ 0.32070312]
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[[ 0.05617606 -0.14993018  0.03754875 ..., -0.13982597  0.16592811
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   0.20638471]]
Progress: 8.4% ... Training loss: 0.320 ... Validation loss: 0.477[[ 0.33543286]
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[[ 0.05723633 -0.15099038  0.03495826 ..., -0.1401634   0.16876327
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   0.20725412]]
Progress: 8.4% ... Training loss: 0.282 ... Validation loss: 0.449[[ 0.33691556]
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[[ 0.05680854 -0.15060471  0.03609087 ..., -0.14004782  0.16762355
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   0.20578977]]
Progress: 8.4% ... Training loss: 0.282 ... Validation loss: 0.450[[ 0.3331592 ]
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[[ 0.05691455 -0.15071761  0.03581172 ..., -0.1400786   0.16785131
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 [ 0.05766689 -0.0320624  -0.07251466 ...,  0.03852364  0.28040801
   0.20673807]]
Progress: 8.4% ... Training loss: 0.284 ... Validation loss: 0.451[[ 0.33834668]
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[[ 0.05691566 -0.15072399  0.03593986 ..., -0.14008551  0.16775641
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 [ 0.05769054 -0.03208374 -0.07259935 ...,  0.03851685  0.28049714
   0.20660625]]
Progress: 8.4% ... Training loss: 0.282 ... Validation loss: 0.452[[ 0.3356118 ]
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[[ 0.05604419 -0.14991637  0.03809367 ..., -0.13985001  0.16551492
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 [-0.19014892 -0.187321   -0.12377993 ...,  0.10489516 -0.0611516
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  -0.23925436]
 [ 0.05762907 -0.03200555 -0.0724707  ...,  0.03854133  0.28044066
   0.20672764]]
Progress: 8.4% ... Training loss: 0.282 ... Validation loss: 0.454[[ 0.34263958]
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[[ 0.05601502 -0.14990707  0.0381719  ..., -0.13984274  0.16564124
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 [ 0.04043671  0.04701179  0.11273836 ..., -0.2444837  -0.03812392
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   0.20691323]]
Progress: 8.4% ... Training loss: 0.284 ... Validation loss: 0.460[[ 0.33693411]
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[[ 0.05587642 -0.149851    0.03836029 ..., -0.13982704  0.16535359
  -0.1923579 ]
 [ 0.04037193  0.04706888  0.11288046 ..., -0.24446733 -0.03829155
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 [ 0.05732992 -0.03174574 -0.07178311 ...,  0.03862136  0.28004207
   0.20731906]]
Progress: 8.4% ... Training loss: 0.282 ... Validation loss: 0.451[[ 0.34648032]
 [-0.28970226]
 [-0.78386014]
 [-0.81201524]
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 [ 1.3234706 ]
 [ 0.42979547]
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[[ 0.05619272 -0.15009767  0.03780825 ..., -0.13992201  0.16618659
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 [ 0.05782433 -0.03215507 -0.07290957 ...,  0.0384992   0.28143416
   0.20619188]]
Progress: 8.4% ... Training loss: 0.290 ... Validation loss: 0.465[[ 0.33315535]
 [-0.30038265]
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 [ 1.31436353]
 [ 0.41906649]
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[[ 0.05538761 -0.14937101  0.03963483 ..., -0.13971502  0.1641032
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  -0.23785557]
 [ 0.05867627 -0.03287055 -0.0748214  ...,  0.03830906  0.28354108
   0.20416898]]
Progress: 8.4% ... Training loss: 0.288 ... Validation loss: 0.454[[ 0.33648161]
 [-0.29726189]
 [-0.79181618]
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 [ 1.31757356]
 [ 0.42213807]
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[[ 0.0556713  -0.14963819  0.03905648 ..., -0.13979307  0.16493038
  -0.19178205]
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  -0.23800102]
 [ 0.05880985 -0.03300236 -0.07512212 ...,  0.03827338  0.28386707
   0.20374949]]
Progress: 8.4% ... Training loss: 0.283 ... Validation loss: 0.451[[ 0.33434522]
 [-0.29907004]
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 [ 1.31550669]
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[[ 0.05544689 -0.14946218  0.0396749  ..., -0.13973864  0.16469727
  -0.19105843]
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  -0.23854705]
 [ 0.05865788 -0.03286155 -0.07473892 ...,  0.0383183   0.28373903
   0.20419741]]
Progress: 8.4% ... Training loss: 0.288 ... Validation loss: 0.453[[ 0.33782647]
 [-0.29594824]
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[[ 0.05579619 -0.14980459  0.03876285 ..., -0.13983391  0.16572269
  -0.1920955 ]
 [ 0.04089523  0.0466059   0.11165242 ..., -0.24459705 -0.03697459
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  -0.23789288]
 [ 0.05855421 -0.03274217 -0.07458653 ...,  0.03834248  0.2835304
   0.20449824]]
Progress: 8.4% ... Training loss: 0.283 ... Validation loss: 0.450[[ 0.34259106]
 [-0.29173985]
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[[ 0.05683587 -0.15070294  0.03640326 ..., -0.14009261  0.16832347
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  -0.23843017]
 [ 0.05853662 -0.03270807 -0.07453643 ...,  0.03836407  0.28380577
   0.20455888]]
Progress: 8.4% ... Training loss: 0.285 ... Validation loss: 0.450[[ 0.3442779 ]
 [-0.29066896]
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[[ 0.05663285 -0.15051458  0.03694724 ..., -0.140034    0.1678323
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  -0.238175  ]
 [ 0.05931038 -0.03337658 -0.07633361 ...,  0.0381842   0.2858201
   0.20279347]]
Progress: 8.4% ... Training loss: 0.287 ... Validation loss: 0.451[[ 0.3332261 ]
 [-0.29950209]
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[[ 0.05547112 -0.14948065  0.03961288 ..., -0.13974982  0.16503081
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 [ 0.04073226  0.04674758  0.11201362 ..., -0.24455716 -0.03730767
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 [ 0.05888104 -0.03300061 -0.07536201 ...,  0.03828556  0.28494954
   0.20386245]]
Progress: 8.5% ... Training loss: 0.286 ... Validation loss: 0.451[[ 0.34653922]
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[[ 0.05577355 -0.14977432  0.03881754 ..., -0.13984912  0.16577293
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 [ 0.04075836  0.0467262   0.1119634  ..., -0.24456441 -0.03723592
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  -0.23836153]
 [ 0.05944904 -0.03353038 -0.07678168 ...,  0.03812652  0.28651085
   0.2024585 ]]
Progress: 8.5% ... Training loss: 0.290 ... Validation loss: 0.457[[ 0.33974767]
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[[ 0.05511199 -0.14918352  0.04040567 ..., -0.13970163  0.16419291
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 ..., 
 [-0.19147493 -0.18621476 -0.12095703 ...,  0.10518823 -0.06470205
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 [ 0.05914557 -0.03326133 -0.07607687 ...,  0.03819675  0.28597272
   0.20311004]]
Progress: 8.5% ... Training loss: 0.281 ... Validation loss: 0.447[[ 0.3356489 ]
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[[ 0.05481369 -0.14893397  0.04113245 ..., -0.13963122  0.1633774
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 [-0.19135656 -0.18631536 -0.12126137 ...,  0.10515829 -0.06442976
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 [ 0.05909296 -0.03320535 -0.07595883 ...,  0.0382126   0.28597188
   0.20320627]]
Progress: 8.5% ... Training loss: 0.284 ... Validation loss: 0.451[[ 0.34448836]
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[[ 0.05526405 -0.14936637  0.04009802 ..., -0.13974865  0.16446694
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 [ 0.04076334  0.04670368  0.11188352 ..., -0.24456557 -0.0372066
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 [-0.19136334 -0.18631233 -0.1212524  ...,  0.10515873 -0.06443319
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  -0.23888781]
 [ 0.05929099 -0.0333678  -0.07641706 ...,  0.03816307  0.28649515
   0.2027854 ]]
Progress: 8.5% ... Training loss: 0.285 ... Validation loss: 0.452[[ 0.34332336]
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[[ 0.05554739 -0.14964947  0.03951821 ..., -0.13981484  0.16501129
  -0.1919701 ]
 [ 0.04098853  0.04651899  0.1113853  ..., -0.24461389 -0.03666618
   0.11815065]
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 [-0.19192348 -0.18584841 -0.12001836 ...,  0.10528589 -0.06578403
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  -0.23901519]
 [ 0.05900622 -0.03311896 -0.07580576 ...,  0.038234    0.28580259
   0.20346218]]
Progress: 8.5% ... Training loss: 0.284 ... Validation loss: 0.452[[ 0.32952668]
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[[ 0.0543623  -0.14861237  0.04242193 ..., -0.13952374  0.16206837
  -0.18931621]
 [ 0.04098483  0.046522    0.11140437 ..., -0.24461167 -0.03668159
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 [-0.19226806 -0.18555261 -0.11925466 ...,  0.10536939 -0.06664004
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  -0.23911497]
 [ 0.05887599 -0.03300619 -0.0755438  ...,  0.03825666  0.28553838
   0.20364053]]
Progress: 8.5% ... Training loss: 0.300 ... Validation loss: 0.466[[ 0.34950341]
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[[ 0.0557603  -0.14990134  0.03911609 ..., -0.1399107   0.1657575
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   0.2030833 ]]
Progress: 8.5% ... Training loss: 0.298 ... Validation loss: 0.471[[ 0.34055945]
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[[ 0.0552513  -0.14942444  0.04043657 ..., -0.13977966  0.16450905
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   0.20432427]]
Progress: 8.5% ... Training loss: 0.282 ... Validation loss: 0.451[[ 0.33589766]
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[[ 0.05494172 -0.14909913  0.04117784 ..., -0.13968754  0.16381863
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  -0.2402986 ]
 [ 0.05777575 -0.03204811 -0.07316434 ...,  0.03852229  0.2836774
   0.20618392]]
Progress: 8.5% ... Training loss: 0.282 ... Validation loss: 0.447[[ 0.33735212]
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[[ 0.05569648 -0.14979074  0.03942772 ..., -0.13988798  0.16569929
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  -0.23985244]
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   0.20566319]]
Progress: 8.5% ... Training loss: 0.282 ... Validation loss: 0.445[[ 0.33082553]
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[[ 0.05517882 -0.14929343  0.0407159  ..., -0.13974651  0.1643772
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   0.20574306]]
Progress: 8.5% ... Training loss: 0.287 ... Validation loss: 0.454[[ 0.33915434]
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 [ 0.05797153 -0.03221    -0.07355544 ...,  0.03847668  0.28428144
   0.20544962]]
Progress: 8.5% ... Training loss: 0.282 ... Validation loss: 0.455[[ 0.34083831]
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[[ 0.0559136  -0.14994475  0.03917036 ..., -0.13994968  0.16604979
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   0.20653432]]
Progress: 8.5% ... Training loss: 0.283 ... Validation loss: 0.457[[ 0.34423695]
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[[ 0.05600264 -0.14997667  0.03915734 ..., -0.1399626   0.16604478
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   0.20567733]]
Progress: 8.5% ... Training loss: 0.291 ... Validation loss: 0.461[[ 0.32397222]
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[[ 0.05452882 -0.14874135  0.04252369 ..., -0.13961423  0.16233664
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   0.20585442]]
Progress: 8.6% ... Training loss: 0.315 ... Validation loss: 0.476[[ 0.34972015]
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[[ 0.05605807 -0.15021287  0.03870123 ..., -0.14009853  0.16638838
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   0.20408091]]
Progress: 8.6% ... Training loss: 0.300 ... Validation loss: 0.479[[ 0.3340337 ]
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[[ 0.05425401 -0.14872036  0.04270908 ..., -0.13969331  0.1620637
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 [ 0.0582728  -0.03251522 -0.07450112 ...,  0.03836269  0.28582116
   0.20462782]]
Progress: 8.6% ... Training loss: 0.288 ... Validation loss: 0.454[[ 0.3398027 ]
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[[ 0.05468654 -0.14913357  0.0417814  ..., -0.13982561  0.16306587
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   0.20370976]]
Progress: 8.6% ... Training loss: 0.281 ... Validation loss: 0.453[[ 0.34376107]
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[[ 0.05501213 -0.1494496   0.04102836 ..., -0.13991851  0.16394091
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   0.20317756]]
Progress: 8.6% ... Training loss: 0.282 ... Validation loss: 0.458[[ 0.33256905]
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[[ 0.05383076 -0.14843947  0.04377657 ..., -0.13963832  0.16121533
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   0.20387942]]
Progress: 8.6% ... Training loss: 0.297 ... Validation loss: 0.459[[ 0.35256379]
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[[ 0.0551216  -0.1495609   0.04081278 ..., -0.13999329  0.1643617
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   0.20312012]]
Progress: 8.6% ... Training loss: 0.303 ... Validation loss: 0.490[[ 0.33746546]
 [-0.29510959]
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[[ 0.05388277 -0.14853215  0.04364262 ..., -0.13973672  0.16172599
  -0.18863073]
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  -0.23868003]
 [ 0.05838557 -0.03265872 -0.07486326 ...,  0.03829729  0.28688903
   0.20423608]]
Progress: 8.6% ... Training loss: 0.284 ... Validation loss: 0.449[[ 0.33371552]
 [-0.29943526]
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 [ 1.32621841]
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[[ 0.05344662 -0.14811652  0.04470731 ..., -0.13961384  0.1608205
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   0.20626947]]
Progress: 8.6% ... Training loss: 0.294 ... Validation loss: 0.455[[ 0.34414172]
 [-0.29000491]
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[[ 0.05440755 -0.14898993  0.04246158 ..., -0.13987117  0.16322669
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  -0.23901436]
 [ 0.05784171 -0.03209929 -0.07351377 ...,  0.03846101  0.28586257
   0.205554  ]]
Progress: 8.6% ... Training loss: 0.283 ... Validation loss: 0.457[[ 0.33820214]
 [-0.29445266]
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 [ 1.33058694]
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[[ 0.05417803 -0.14878193  0.04302718 ..., -0.13981194  0.16252276
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  -0.23814493]
 [ 0.05779562 -0.03205229 -0.07339041 ...,  0.03847676  0.28582508
   0.20565026]]
Progress: 8.6% ... Training loss: 0.283 ... Validation loss: 0.452[[ 0.33970012]
 [-0.2920684 ]
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 [ 1.33195032]
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[[ 0.05393544 -0.14852277  0.04364594 ..., -0.13975117  0.1616652
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  -0.23815859]
 [ 0.05864594 -0.03279575 -0.07540041 ...,  0.03825659  0.28796014
   0.20365325]]
Progress: 8.6% ... Training loss: 0.281 ... Validation loss: 0.452[[ 0.34820961]
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[[ 0.05466194 -0.1491439   0.04204186 ..., -0.13993358  0.16349448
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  -0.23929658]
 [ 0.05901619 -0.03312429 -0.07622452 ...,  0.03816141  0.28895631
   0.2026165 ]]
Progress: 8.6% ... Training loss: 0.292 ... Validation loss: 0.465[[ 0.33280545]
 [-0.29835   ]
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[[ 0.05377948 -0.14842556  0.04402205 ..., -0.13971587  0.16179264
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  -0.23820498]
 [ 0.0583345  -0.0325242  -0.07462074 ...,  0.03832877  0.28752708
   0.20414438]]
Progress: 8.6% ... Training loss: 0.292 ... Validation loss: 0.455[[ 0.34034306]
 [-0.29255452]
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[[ 0.05459406 -0.14912773  0.04226541 ..., -0.13993363  0.16378288
  -0.189993  ]
 [ 0.04082916  0.0466808   0.1116457  ..., -0.24455301 -0.03693287
   0.11813552]
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  -0.23873371]
 [ 0.05897621 -0.03312003 -0.07614751 ...,  0.03814391  0.2891283
   0.20254278]]
Progress: 8.6% ... Training loss: 0.281 ... Validation loss: 0.451[[ 0.34348837]
 [-0.29000003]
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[[ 0.05513101 -0.14958829  0.04111446 ..., -0.14007185  0.16482183
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 [ 0.04106617  0.04647793  0.1110987  ..., -0.24461325 -0.0363409
   0.11758867]
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 [-0.19167692 -0.18628169 -0.12087429 ...,  0.10509015 -0.0659332
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  -0.23888099]
 [ 0.0584195  -0.03264064 -0.07485442 ...,  0.03828267  0.28796998
   0.20384536]]
Progress: 8.7% ... Training loss: 0.282 ... Validation loss: 0.455[[ 0.33836527]
 [-0.29357882]
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[[ 0.05465031 -0.14915425  0.04233791 ..., -0.13994015  0.1634361
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 [-0.19171537 -0.18625175 -0.12076927 ...,  0.10510152 -0.06612851
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  -0.24007757]
 [ 0.05824215 -0.03249151 -0.07439809 ...,  0.03832851  0.28767242
   0.20424271]]
Progress: 8.7% ... Training loss: 0.282 ... Validation loss: 0.453[[ 0.33975606]
 [-0.29106179]
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[[ 0.05476114 -0.14922098  0.04221221 ..., -0.13995774  0.16389451
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  -0.24106992]
 [ 0.05875679 -0.03294823 -0.07554529 ...,  0.03818937  0.28895368
   0.20305813]]
Progress: 8.7% ... Training loss: 0.281 ... Validation loss: 0.452[[ 0.33786809]
 [-0.29404687]
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[[ 0.05461085 -0.14909254  0.04270368 ..., -0.1399229   0.16365491
  -0.18973562]
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 ..., 
 [-0.19212278 -0.1859037  -0.11987817 ...,  0.10519665 -0.06712524
  -0.03646873]
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  -0.2408324 ]
 [ 0.058047   -0.03232458 -0.07388336 ...,  0.03838081  0.28740331
   0.20475953]]
Progress: 8.7% ... Training loss: 0.282 ... Validation loss: 0.450[[ 0.33606527]
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[[ 0.05500876 -0.14942266  0.04186593 ..., -0.14002656  0.16429723
  -0.19083514]
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 [-0.19197032 -0.18602909 -0.1202421  ...,  0.10515394 -0.0668822
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  -0.24119404]
 [ 0.05792386 -0.03220546 -0.07368414 ...,  0.0384142   0.28712156
   0.20502835]]
Progress: 8.7% ... Training loss: 0.281 ... Validation loss: 0.448[[ 0.34420894]
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[[ 0.05484777 -0.14926197  0.04231588 ..., -0.13996958  0.16380426
  -0.19059702]
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 [ 0.05827094 -0.03251471 -0.07448692 ...,  0.03831962  0.28802161
   0.2042018 ]]
Progress: 8.7% ... Training loss: 0.285 ... Validation loss: 0.463[[ 0.33223131]
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[[ 0.05460688 -0.1490229   0.04295443 ..., -0.13990178  0.1632196
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   0.20548353]]
Progress: 8.7% ... Training loss: 0.287 ... Validation loss: 0.456[[ 0.34622201]
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[[ 0.0546096  -0.14903759  0.04286088 ..., -0.13989897  0.1632501
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   0.20540371]]
Progress: 8.7% ... Training loss: 0.290 ... Validation loss: 0.466[[ 0.33641599]
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   0.20742231]]
Progress: 8.7% ... Training loss: 0.281 ... Validation loss: 0.448[[ 0.3418708 ]
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  -0.24218714]
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   0.20846828]]
Progress: 8.7% ... Training loss: 0.282 ... Validation loss: 0.451[[ 0.33266132]
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[[ 0.05350662 -0.14813752  0.04543258 ..., -0.13961977  0.16114911
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   0.20935136]]
Progress: 8.7% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.33415733]
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[[ 0.05339281 -0.14805656  0.04572981 ..., -0.13958844  0.1608405
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   0.20878082]]
Progress: 8.7% ... Training loss: 0.283 ... Validation loss: 0.449[[ 0.33371238]
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   0.20963088]]
Progress: 8.7% ... Training loss: 0.284 ... Validation loss: 0.451[[ 0.34069203]
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   0.20801666]]
Progress: 8.7% ... Training loss: 0.280 ... Validation loss: 0.451[[ 0.3267023 ]
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   0.20875179]]
Progress: 8.7% ... Training loss: 0.309 ... Validation loss: 0.472[[ 0.35447338]
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   0.20634009]]
Progress: 8.8% ... Training loss: 0.313 ... Validation loss: 0.502[[ 0.33706156]
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[[ 0.05454661 -0.14935188  0.04277107 ..., -0.14008304  0.16398119
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 [ 0.05678885 -0.03128954 -0.0714727  ...,  0.03862277  0.28602917
   0.20707427]]
Progress: 8.8% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.34113838]
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[[ 0.05532557 -0.14999556  0.04110864 ..., -0.14030363  0.16583414
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   0.20654668]]
Progress: 8.8% ... Training loss: 0.280 ... Validation loss: 0.453[[ 0.33770648]
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[[ 0.05540627 -0.1501026   0.04095355 ..., -0.14034055  0.16608554
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   0.20533026]]
Progress: 8.8% ... Training loss: 0.280 ... Validation loss: 0.449[[ 0.33710951]
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[[ 0.05543678 -0.1501164   0.040738   ..., -0.14032612  0.16599829
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   0.20544133]]
Progress: 8.8% ... Training loss: 0.280 ... Validation loss: 0.448[[ 0.34002555]
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[[ 0.05609404 -0.15067848  0.03930013 ..., -0.14051684  0.16757414
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   0.20573171]]
Progress: 8.8% ... Training loss: 0.280 ... Validation loss: 0.450[[ 0.33313847]
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[[ 0.05540944 -0.15007472  0.04098799 ..., -0.14033582  0.16594031
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   0.20572813]]
Progress: 8.8% ... Training loss: 0.284 ... Validation loss: 0.449[[ 0.34338626]
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[[ 0.05554892 -0.15020991  0.04060364 ..., -0.14038862  0.16630483
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   0.20540439]]
Progress: 8.8% ... Training loss: 0.283 ... Validation loss: 0.452[[ 0.34533973]
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[[ 0.05566211 -0.1502972   0.04028497 ..., -0.14041298  0.16658612
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  -0.24331252]
 [ 0.05760586 -0.03193664 -0.07370614 ...,  0.03839678  0.28849928
   0.2050593 ]]
Progress: 8.8% ... Training loss: 0.286 ... Validation loss: 0.455[[ 0.33709953]
 [-0.29463423]
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[[ 0.05494279 -0.14972403  0.04189394 ..., -0.1402415   0.16506326
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  -0.24253164]
 [ 0.05681559 -0.03125374 -0.07187652 ...,  0.03860229  0.28676909
   0.20683995]]
Progress: 8.8% ... Training loss: 0.282 ... Validation loss: 0.446[[ 0.34427137]
 [-0.28712105]
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[[ 0.05543586 -0.15013606  0.04082991 ..., -0.14036308  0.16619877
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  -0.24343996]
 [ 0.05726952 -0.03164597 -0.0729986  ...,  0.03846834  0.28808066
   0.20563175]]
Progress: 8.8% ... Training loss: 0.283 ... Validation loss: 0.451[[ 0.34040692]
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[[ 0.05548416 -0.15017684  0.04070097 ..., -0.14037234  0.16638962
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   0.2060407 ]]
Progress: 8.8% ... Training loss: 0.281 ... Validation loss: 0.449[[ 0.34417045]
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[[ 0.05646665 -0.15102185  0.03859148 ..., -0.14063994  0.16878441
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 [ 0.0573809  -0.0317521  -0.07339024 ...,  0.03843554  0.28861663
   0.20494829]]
Progress: 8.8% ... Training loss: 0.283 ... Validation loss: 0.451[[ 0.3328545 ]
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[[ 0.05635052 -0.15090514  0.03895722 ..., -0.14060834  0.16862027
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   0.20400324]]
Progress: 8.8% ... Training loss: 0.284 ... Validation loss: 0.448[[ 0.33314828]
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[[ 0.05635346 -0.15088105  0.03900825 ..., -0.14060581  0.16860355
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   0.20306641]]
Progress: 8.8% ... Training loss: 0.283 ... Validation loss: 0.445[[ 0.33395976]
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[[ 0.05631295 -0.15086775  0.03920127 ..., -0.14059596  0.16832888
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   0.20457906]]
Progress: 8.9% ... Training loss: 0.281 ... Validation loss: 0.446[[ 0.33355983]
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[[ 0.0559742  -0.15055041  0.0400866  ..., -0.14049566  0.1672901
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   0.20450104]]
Progress: 8.9% ... Training loss: 0.282 ... Validation loss: 0.445[[ 0.34685046]
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[[ 0.05700539 -0.15148458  0.03759579 ..., -0.14079086  0.1699485
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 [-0.19239882 -0.18577096 -0.1195746  ...,  0.10518888 -0.06849468
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 [ 0.05807645 -0.03225259 -0.07494218 ...,  0.03826134  0.29075064
   0.2031479 ]]
Progress: 8.9% ... Training loss: 0.294 ... Validation loss: 0.459[[ 0.33933977]
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[[ 0.05664289 -0.15116264  0.03838085 ..., -0.14067735  0.16929495
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  -0.24031075]
 [ 0.0572549  -0.03154899 -0.07309378 ...,  0.03847257  0.28905996
   0.20506486]]
Progress: 8.9% ... Training loss: 0.280 ... Validation loss: 0.442[[ 0.32683936]
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[[ 0.05635805 -0.15085394  0.03927285 ..., -0.14059001  0.16844514
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 [-0.19165882 -0.18638328 -0.12109264 ...,  0.10498599 -0.06686757
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 [ 0.05678193 -0.03112466 -0.07200265 ...,  0.03860254  0.28813393
   0.20617776]]
Progress: 8.9% ... Training loss: 0.296 ... Validation loss: 0.457[[ 0.3395129 ]
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[[ 0.05656359 -0.15103471  0.03889668 ..., -0.14065806  0.16892864
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   0.20507289]]
Progress: 8.9% ... Training loss: 0.280 ... Validation loss: 0.450[[ 0.33530941]
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[[ 0.05690607 -0.15131611  0.03821999 ..., -0.14074317  0.16983927
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   0.20517545]]
Progress: 8.9% ... Training loss: 0.279 ... Validation loss: 0.448[[ 0.33235992]
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[[ 0.05647166 -0.15090119  0.03943774 ..., -0.14062783  0.16888716
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   0.20533049]]
Progress: 8.9% ... Training loss: 0.283 ... Validation loss: 0.452[[ 0.33249037]
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[[ 0.05636601 -0.1507991   0.03965414 ..., -0.14060327  0.16874838
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   0.20561117]]
Progress: 8.9% ... Training loss: 0.283 ... Validation loss: 0.452[[ 0.33751083]
 [-0.29118229]
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[[ 0.05686537 -0.15126009  0.03848277 ..., -0.14075164  0.16985428
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   0.20508919]]
Progress: 8.9% ... Training loss: 0.279 ... Validation loss: 0.453[[ 0.33480391]
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   0.20582118]]
Progress: 8.9% ... Training loss: 0.280 ... Validation loss: 0.449[[ 0.3402015 ]
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   0.2043611 ]]
Progress: 8.9% ... Training loss: 0.279 ... Validation loss: 0.452[[ 0.35483055]
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[[ 0.05787904 -0.15222111  0.03619475 ..., -0.14103659  0.17257083
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   0.2018173 ]]
Progress: 8.9% ... Training loss: 0.320 ... Validation loss: 0.504[[ 0.32950246]
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[[ 0.05530564 -0.15021146  0.04181194 ..., -0.14046004  0.16661261
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   0.20300925]]
Progress: 8.9% ... Training loss: 0.303 ... Validation loss: 0.465[[ 0.34597622]
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[[ 0.05613706 -0.15097373  0.03990293 ..., -0.14072075  0.16862872
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   0.20023252]]
Progress: 8.9% ... Training loss: 0.281 ... Validation loss: 0.459[[ 0.34816107]
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[[ 0.05579587 -0.15063125  0.04077053 ..., -0.14061274  0.16820685
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 [ 0.05881399 -0.03302299 -0.07700589 ...,  0.03797865  0.29441852
   0.20085407]]
Progress: 9.0% ... Training loss: 0.286 ... Validation loss: 0.465[[ 0.34772727]
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[[ 0.05666268 -0.1512877   0.03898111 ..., -0.14082756  0.17041791
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 [ 0.05870964 -0.03292111 -0.07671646 ...,  0.03800525  0.29437447
   0.20115565]]
Progress: 9.0% ... Training loss: 0.289 ... Validation loss: 0.467[[ 0.33866325]
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[[ 0.05551098 -0.15031818  0.04168396 ..., -0.1405427   0.16765458
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 [ 0.05829224 -0.03255786 -0.075809   ...,  0.03811106  0.29356025
   0.20202091]]
Progress: 9.0% ... Training loss: 0.279 ... Validation loss: 0.449[[ 0.34564456]
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[[ 0.05634796 -0.1510471   0.03979759 ..., -0.14079038  0.169696
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 [-0.19197011 -0.18623568 -0.12059121 ...,  0.10498324 -0.06783235
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  -0.24251003]
 [ 0.05884275 -0.03303852 -0.07712469 ...,  0.03796095  0.29496665
   0.20067444]]
Progress: 9.0% ... Training loss: 0.283 ... Validation loss: 0.458[[ 0.3390153 ]
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[[ 0.05600714 -0.15077602  0.04062528 ..., -0.14070689  0.16856934
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 [ 0.0587845  -0.0329956  -0.0771284  ...,  0.03797614  0.29509797
   0.20061544]]
Progress: 9.0% ... Training loss: 0.280 ... Validation loss: 0.450[[ 0.33298583]
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   0.19964423]]
Progress: 9.0% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.34485905]
 [-0.28918339]
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 [ 1.35200327]
 [ 0.42268746]
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[[ 0.0564994  -0.1512564   0.03943656 ..., -0.14085393  0.16962781
  -0.1962287 ]
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 [ 0.05915282 -0.03331694 -0.07803346 ...,  0.03787499  0.2961175
   0.19976093]]
Progress: 9.0% ... Training loss: 0.281 ... Validation loss: 0.461[[ 0.34604898]
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[[ 0.05692368 -0.15159815  0.03852712 ..., -0.14097899  0.1709355
  -0.19718408]
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  -0.24269013]
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   0.19852983]]
Progress: 9.0% ... Training loss: 0.282 ... Validation loss: 0.457[[ 0.34222515]
 [-0.29314026]
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[[ 0.05721528 -0.15184782  0.03779002 ..., -0.1410507   0.17145103
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  -0.24248233]
 [ 0.05892715 -0.03307052 -0.07756658 ...,  0.03793671  0.29609167
   0.20029901]]
Progress: 9.0% ... Training loss: 0.278 ... Validation loss: 0.449[[ 0.33854376]
 [-0.29646577]
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 [ 0.41975615]
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[[ 0.05730845 -0.15189819  0.03778211 ..., -0.14107849  0.17186868
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  -0.24231862]
 [ 0.0586074  -0.03278425 -0.076853   ...,  0.03802656  0.29555071
   0.20102043]]
Progress: 9.0% ... Training loss: 0.279 ... Validation loss: 0.444[[ 0.34724127]
 [-0.28762472]
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[[ 0.05783578 -0.15236168  0.03672837 ..., -0.14121827  0.17308262
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  -0.24335169]
 [ 0.05913881 -0.03325065 -0.0780983  ...,  0.03788095  0.29690478
   0.19977569]]
Progress: 9.0% ... Training loss: 0.287 ... Validation loss: 0.460[[ 0.33879269]
 [-0.29749587]
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[[ 0.0575875  -0.15218312  0.03727935 ..., -0.14116674  0.17264311
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  -0.24233314]
 [ 0.05933529 -0.03341562 -0.07856466 ...,  0.03783439  0.29745926
   0.19938386]]
Progress: 9.0% ... Training loss: 0.279 ... Validation loss: 0.446[[ 0.33676618]
 [-0.30016069]
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[[ 0.0567225  -0.15140641  0.03934078 ..., -0.14091594  0.17065666
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   0.19915843]]
Progress: 9.0% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.341704  ]
 [-0.29613253]
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[[ 0.05674385 -0.15143637  0.03922906 ..., -0.14091217  0.1707583
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  -0.24278138]
 [ 0.05958299 -0.0336345  -0.07911953 ...,  0.03776998  0.29844396
   0.19885689]]
Progress: 9.0% ... Training loss: 0.280 ... Validation loss: 0.451[[ 0.34888183]
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[[ 0.0574476  -0.15199291  0.03780224 ..., -0.14108876  0.17272621
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 [-0.19289393 -0.18553444 -0.11857092 ...,  0.10519139 -0.07053395
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  -0.24299574]
 [ 0.05975113 -0.03379158 -0.07952808 ...,  0.03771926  0.29910587
   0.1984158 ]]
Progress: 9.0% ... Training loss: 0.285 ... Validation loss: 0.457[[ 0.32951071]
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[[ 0.05658959 -0.15124855  0.03971748 ..., -0.14086183  0.17058202
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 [-0.19315754 -0.18532157 -0.11809231 ...,  0.10525404 -0.07113966
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 [ 0.05918888 -0.03330997 -0.07824911 ...,  0.0378682   0.29790147
   0.19965348]]
Progress: 9.1% ... Training loss: 0.304 ... Validation loss: 0.465[[ 0.34807963]
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[[ 0.05806541 -0.15261404  0.0363131  ..., -0.14130559  0.17429727
  -0.20061447]
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   0.11565121]
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 [-0.19295661 -0.18551148 -0.11848513 ...,  0.10519173 -0.07065576
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  -0.24323075]
 [ 0.059899   -0.0339767  -0.07994713 ...,  0.03765428  0.29974363
   0.19781138]]
Progress: 9.1% ... Training loss: 0.286 ... Validation loss: 0.457[[ 0.33425489]
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[[ 0.05695035 -0.15169253  0.03884866 ..., -0.14103085  0.17183318
  -0.19806114]
 [ 0.04167994  0.04595793  0.10913799 ..., -0.24478078 -0.03398258
   0.11565121]
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 [-0.19303756 -0.18544221 -0.11831102 ...,  0.1052125  -0.07090514
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  -0.24218881]
 [ 0.0590417  -0.03324096 -0.07801235 ...,  0.03786601  0.29805587
   0.19984735]]
Progress: 9.1% ... Training loss: 0.289 ... Validation loss: 0.453[[ 0.34940861]
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[[ 0.05785441 -0.15252586  0.03665162 ..., -0.14129489  0.17402042
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   0.11539797]
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 ..., 
 [-0.19320463 -0.18529138 -0.11791188 ...,  0.10526161 -0.0713139
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  -0.24316006]
 [ 0.05931967 -0.03347521 -0.0786812  ...,  0.03779748  0.2989128
   0.19922141]]
Progress: 9.1% ... Training loss: 0.286 ... Validation loss: 0.458[[ 0.33610133]
 [-0.30062901]
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[[ 0.05699196 -0.15184219  0.03862013 ..., -0.14108728  0.17203599
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 [-0.19344877 -0.18508933 -0.11736025 ...,  0.10532334 -0.07190139
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   0.20008513]]
Progress: 9.1% ... Training loss: 0.286 ... Validation loss: 0.449[[ 0.34585604]
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[[ 0.05728285 -0.15212028  0.03780703 ..., -0.14118944  0.17287955
  -0.19935644]
 [ 0.04184553  0.04580421  0.10872745 ..., -0.24483301 -0.03357599
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  -0.24287716]
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   0.19963821]]
Progress: 9.1% ... Training loss: 0.279 ... Validation loss: 0.450[[ 0.35021769]
 [-0.28894507]
 [-0.78485487]
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 [ 1.37233997]
 [ 0.42468019]
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[[ 0.05770205 -0.15250791  0.03694615 ..., -0.14130265  0.17390521
  -0.20023585]
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  -0.24286362]
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   0.19989094]]
Progress: 9.1% ... Training loss: 0.284 ... Validation loss: 0.461[[ 0.34289287]
 [-0.29598143]
 [-0.79136065]
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 [ 1.36674832]
 [ 0.41772205]
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[[ 0.05694236 -0.15186899  0.03869872 ..., -0.14111448  0.17209822
  -0.19857361]
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  -0.24277597]
 [ 0.0588485  -0.0330984  -0.07774709 ...,  0.03790438  0.29846479
   0.20019588]]
Progress: 9.1% ... Training loss: 0.279 ... Validation loss: 0.448[[ 0.34910872]
 [-0.29082321]
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 [ 1.37253691]
 [ 0.42247376]
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[[ 0.0570583  -0.15194856  0.03853739 ..., -0.14114171  0.17224529
  -0.19894703]
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  -0.24294519]
 [ 0.05945746 -0.03362893 -0.0791106  ...,  0.03773175  0.30000796
   0.19883939]]
Progress: 9.1% ... Training loss: 0.280 ... Validation loss: 0.454[[ 0.34504379]
 [-0.29460091]
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 [ 1.37251782]
 [ 0.41962248]
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[[ 0.0573544  -0.15218587  0.03809638 ..., -0.14122196  0.17277553
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  -0.24307831]
 [ 0.05959542 -0.03373862 -0.07942776 ...,  0.03769245  0.30045626
   0.19857766]]
Progress: 9.1% ... Training loss: 0.278 ... Validation loss: 0.447[[ 0.345323  ]
 [-0.29369388]
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 [ 1.36905985]
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[[ 0.0576537  -0.1524884   0.03748076 ..., -0.14130827  0.17345835
  -0.20021007]
 [ 0.04182001  0.04582122  0.10873329 ..., -0.24481925 -0.03363559
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 [-0.19344525 -0.18512358 -0.11711582 ...,  0.10531483 -0.07204276
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  -0.24305791]
 [ 0.06002415 -0.03411736 -0.08044537 ...,  0.03757013  0.30154755
   0.19762431]]
Progress: 9.1% ... Training loss: 0.278 ... Validation loss: 0.451[[ 0.35054275]
 [-0.28894773]
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 [-0.80932887]
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 [ 1.37628308]
 [ 0.42199915]
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[[ 0.05827593 -0.15301289  0.03610722 ..., -0.14147618  0.17464687
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  -0.24272215]
 [ 0.06033746 -0.03439265 -0.08119246 ...,  0.03749005  0.30228681
   0.19678567]]
Progress: 9.1% ... Training loss: 0.284 ... Validation loss: 0.459[[ 0.33666073]
 [-0.30105972]
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[[ 0.0573955  -0.15223395  0.03802209 ..., -0.14124461  0.17251812
  -0.20019862]
 [ 0.04202782  0.04565176  0.10825488 ..., -0.24486853 -0.03314571
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  -0.24115159]
 [ 0.06010966 -0.03417556 -0.08076399 ...,  0.03756109  0.30187299
   0.19717433]]
Progress: 9.1% ... Training loss: 0.290 ... Validation loss: 0.451[[ 0.34510461]
 [-0.29193863]
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[[ 0.05712023 -0.15197251  0.03882994 ..., -0.14116486  0.17217462
  -0.19930279]
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  -0.24105343]
 [ 0.0603917  -0.03444602 -0.08150947 ...,  0.03745999  0.3027507
   0.19636809]]
Progress: 9.1% ... Training loss: 0.277 ... Validation loss: 0.447[[ 0.33695037]
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[[ 0.0560568  -0.15104216  0.04140675 ..., -0.14085679  0.16971926
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 [ 0.04211442  0.04557821  0.10801923 ..., -0.24489267 -0.03288482
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 [-0.19277806 -0.1856959  -0.11852697 ...,  0.10512976 -0.07060695
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  -0.24140928]
 [ 0.05999511 -0.03410329 -0.08061938 ...,  0.03757382  0.30189631
   0.19727264]]
Progress: 9.1% ... Training loss: 0.289 ... Validation loss: 0.452[[ 0.34650699]
 [-0.28941849]
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[[ 0.05709652 -0.15195569  0.03934036 ..., -0.14116929  0.17204132
  -0.19897179]
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 [-0.19278535 -0.18569185 -0.1184969  ...,  0.10513237 -0.07062383
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  -0.24318747]
 [ 0.05974246 -0.03386175 -0.0799892  ...,  0.0376581   0.30148312
   0.19791167]]
Progress: 9.2% ... Training loss: 0.278 ... Validation loss: 0.455[[ 0.33906699]
 [-0.29552075]
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[[ 0.056626   -0.15154961  0.04032164 ..., -0.14103125  0.17116272
  -0.1980887 ]
 [ 0.0418072   0.04584572  0.10872479 ..., -0.24480037 -0.03356951
   0.11518829]
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   0.41473475]
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 [-0.19318983 -0.18535419 -0.11758987 ...,  0.10523772 -0.07160787
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  -0.24334337]
 [ 0.05914631 -0.03333245 -0.07865847 ...,  0.0378465   0.30052917
   0.1993016 ]]
Progress: 9.2% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.34683547]
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[[ 0.05788389 -0.15264935  0.03746394 ..., -0.14140937  0.17430313
  -0.20113727]
 [ 0.04222564  0.04547867  0.10776242 ..., -0.24492451 -0.03254294
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 ..., 
 [-0.19324533 -0.18530733 -0.11751533 ...,  0.10525063 -0.071721
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  -0.2444156 ]
 [ 0.05940306 -0.03353729 -0.07924835 ...,  0.03777058  0.30125233
   0.19851337]]
Progress: 9.2% ... Training loss: 0.279 ... Validation loss: 0.460[[ 0.34209342]
 [-0.29289232]
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[[ 0.05766587 -0.15246154  0.0379244  ..., -0.1413429   0.17377443
  -0.2006793 ]
 [ 0.04235794  0.04537045  0.10746655 ..., -0.24495953 -0.03221354
   0.11397873]
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   0.41303376]
 ..., 
 [-0.19341311 -0.18516798 -0.11711691 ...,  0.10529673 -0.07218624
  -0.03501233]
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  -0.24443542]
 [ 0.05954295 -0.03365427 -0.07959025 ...,  0.03774225  0.30167015
   0.19814067]]
Progress: 9.2% ... Training loss: 0.279 ... Validation loss: 0.452[[ 0.34373368]
 [-0.29286104]
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[[ 0.05826922 -0.15300111  0.03662768 ..., -0.14151143  0.17530124
  -0.20213412]
 [ 0.04255598  0.04520739  0.10700879 ..., -0.24501625 -0.03172695
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 ..., 
 [-0.19320163 -0.18536345 -0.11755919 ...,  0.10522752 -0.0717061
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  -0.24398336]
 [ 0.05888397 -0.03307038 -0.07810523 ...,  0.03795156  0.30040337
   0.19971166]]
Progress: 9.2% ... Training loss: 0.278 ... Validation loss: 0.452[[ 0.34083234]
 [-0.29588262]
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[[ 0.05836233 -0.15309031  0.03641458 ..., -0.14155228  0.17549848
  -0.2023706 ]
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  -0.2441148 ]
 [ 0.05892015 -0.03308767 -0.07812288 ...,  0.03795011  0.30054063
   0.19968133]]
Progress: 9.2% ... Training loss: 0.280 ... Validation loss: 0.449[[ 0.34439935]
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 [-0.78846918]
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[[ 0.05904306 -0.15367454  0.03492782 ..., -0.14176879  0.17711567
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   0.20063181]]
Progress: 9.2% ... Training loss: 0.277 ... Validation loss: 0.456[[ 0.33946968]
 [-0.29585856]
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[[ 0.05852211 -0.15322488  0.03617918 ..., -0.14160741  0.1758026
  -0.2027521 ]
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  -0.24300345]
 [ 0.05918294 -0.03328273 -0.07867868 ...,  0.03788672  0.30128445
   0.19918464]]
Progress: 9.2% ... Training loss: 0.281 ... Validation loss: 0.448[[ 0.34993429]
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[[ 0.05902901 -0.15368369  0.03506707 ..., -0.14175828  0.17697151
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 [ 0.05997718 -0.03398145 -0.08052409 ...,  0.03765251  0.30318     0.19736791]]
Progress: 9.2% ... Training loss: 0.284 ... Validation loss: 0.472[[ 0.34020558]
 [-0.29460474]
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[[ 0.0589596  -0.15360689  0.03530092 ..., -0.14172871  0.17678322
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 [ 0.05913326 -0.03325461 -0.07863001 ...,  0.03788116  0.30135605
   0.19904898]]
Progress: 9.2% ... Training loss: 0.279 ... Validation loss: 0.447[[ 0.34691844]
 [-0.28879757]
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[[ 0.05927298 -0.15386898  0.03455305 ..., -0.14181913  0.17772331
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 [ 0.05916177 -0.03325363 -0.07872219 ...,  0.03788964  0.30166406
   0.1989558 ]]
Progress: 9.2% ... Training loss: 0.281 ... Validation loss: 0.455[[ 0.34052887]
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[[ 0.05860471 -0.15329605  0.03604516 ..., -0.14163794  0.17629451
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 [ 0.05934095 -0.03337707 -0.07911294 ...,  0.03785136  0.30218757
   0.19864602]]
Progress: 9.2% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.34971862]
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[[ 0.05965333 -0.15423292  0.03376403 ..., -0.1419417   0.17861202
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 [ 0.05993046 -0.03390467 -0.0804786  ...,  0.03767854  0.30369165
   0.19730854]]
Progress: 9.2% ... Training loss: 0.284 ... Validation loss: 0.467[[ 0.34372347]
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[[ 0.05969379 -0.15421472  0.03373255 ..., -0.14195061  0.17872462
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 [-0.19217807 -0.18624199 -0.1198321  ...,  0.10494077 -0.0695973
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 [ 0.05929593 -0.03333701 -0.07908659 ...,  0.03785556  0.30234055
   0.19861044]]
Progress: 9.2% ... Training loss: 0.277 ... Validation loss: 0.450[[ 0.3364666 ]
 [-0.29980034]
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[[ 0.05904282 -0.15368695  0.03532433 ..., -0.14178511  0.17701312
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 [ 0.05913388 -0.03317724 -0.07877502 ...,  0.03790441  0.30212588
   0.19897214]]
Progress: 9.2% ... Training loss: 0.285 ... Validation loss: 0.444[[ 0.35097494]
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[[ 0.06026102 -0.15477764  0.03261787 ..., -0.14217762  0.17984144
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 [ 0.05945964 -0.03347786 -0.07950773 ...,  0.03779302  0.30295307
   0.19814465]]
Progress: 9.3% ... Training loss: 0.285 ... Validation loss: 0.476[[ 0.34311891]
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[[ 0.05998717 -0.1545724   0.03330659 ..., -0.14210622  0.1791522
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 [ 0.05964765 -0.0336228  -0.07991221 ...,  0.03774656  0.30349744
   0.19773065]]
Progress: 9.3% ... Training loss: 0.277 ... Validation loss: 0.451[[ 0.34718469]
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[[ 0.06017012 -0.15472492  0.03299588 ..., -0.14216509  0.17967115
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 [-0.19209488 -0.18633589 -0.12001523 ...,  0.10491666 -0.0696967
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 [ 0.05960596 -0.0335761  -0.07974602 ...,  0.03776094  0.30354532
   0.19783566]]
Progress: 9.3% ... Training loss: 0.278 ... Validation loss: 0.459[[ 0.33741053]
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[[ 0.05929945 -0.15397418  0.03508792 ..., -0.1419158   0.17746127
  -0.2040595 ]
 [ 0.04198512  0.04568443  0.10821119 ..., -0.24487301 -0.03279012
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 [-0.19241835 -0.18605907 -0.11934194 ...,  0.10501375 -0.07049736
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  -0.24123675]
 [ 0.05915624 -0.03316987 -0.0786557  ...,  0.03789251  0.30263362
   0.19883793]]
Progress: 9.3% ... Training loss: 0.285 ... Validation loss: 0.443[[ 0.34840434]
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[[ 0.05950621 -0.15416024  0.03463564 ..., -0.14196983  0.17796871
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   0.19831152]]
Progress: 9.3% ... Training loss: 0.279 ... Validation loss: 0.461[[ 0.33603261]
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[[ 0.05816528 -0.15297564  0.03766025 ..., -0.1416026   0.17487692
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   0.19894881]]
Progress: 9.3% ... Training loss: 0.292 ... Validation loss: 0.448[[ 0.35941269]
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[[ 0.05997125 -0.15453874  0.03347354 ..., -0.14215446  0.17896462
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   0.19848108]]
Progress: 9.3% ... Training loss: 0.313 ... Validation loss: 0.513[[ 0.34051568]
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[[ 0.05941688 -0.1540952   0.03470573 ..., -0.14199862  0.17774066
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   0.1993472 ]]
Progress: 9.3% ... Training loss: 0.281 ... Validation loss: 0.438[[ 0.35403063]
 [-0.28463479]
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[[ 0.06053178 -0.15511263  0.03221249 ..., -0.14234765  0.18038799
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   0.19852884]]
Progress: 9.3% ... Training loss: 0.293 ... Validation loss: 0.468[[ 0.33630029]
 [-0.29988827]
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[[ 0.05872671 -0.15362159  0.03624205 ..., -0.14188204  0.17638382
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   0.19972832]]
Progress: 9.3% ... Training loss: 0.292 ... Validation loss: 0.446[[ 0.35659157]
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[[ 0.06000467 -0.15476098  0.03321396 ..., -0.14227975  0.17950046
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   0.19787053]]
Progress: 9.3% ... Training loss: 0.302 ... Validation loss: 0.480[[ 0.32946079]
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[[ 0.05732784 -0.15266355  0.0390218  ..., -0.14163398  0.17334519
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   0.1981789 ]]
Progress: 9.3% ... Training loss: 0.331 ... Validation loss: 0.477[[ 0.35794019]
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[[ 0.05900712 -0.15424221  0.03506907 ..., -0.1422113   0.17755405
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   0.19721413]]
Progress: 9.3% ... Training loss: 0.298 ... Validation loss: 0.486[[ 0.33619802]
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[[ 0.05619785 -0.1519906   0.04127332 ..., -0.14152085  0.17078566
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 [ 0.05931566 -0.03339257 -0.07935556 ...,  0.03777201  0.3041084
   0.1981209 ]]
Progress: 9.3% ... Training loss: 0.303 ... Validation loss: 0.457[[ 0.35237492]
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[[ 0.0569736  -0.15269865  0.03952887 ..., -0.14175329  0.1726948
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 [ 0.05948567 -0.0335304  -0.07977471 ...,  0.03772288  0.30470844
   0.19768797]]
Progress: 9.3% ... Training loss: 0.279 ... Validation loss: 0.463[[ 0.34303403]
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[[ 0.05623284 -0.1520629   0.04117475 ..., -0.14155381  0.17111459
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 [ 0.05928876 -0.03334036 -0.07926012 ...,  0.03777639  0.30452063
   0.19811111]]
Progress: 9.4% ... Training loss: 0.281 ... Validation loss: 0.447[[ 0.34211177]
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[[ 0.05580803 -0.15169705  0.04215381 ..., -0.14144482  0.17002116
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 [ 0.042204    0.04544403  0.10754705 ..., -0.24496813 -0.03210604
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 [-0.19305167 -0.18585982 -0.11839611 ...,  0.10496323 -0.07187164
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  -0.23849084]
 [ 0.05942607 -0.03345641 -0.07967987 ...,  0.03772117  0.30496951
   0.19748958]]
Progress: 9.4% ... Training loss: 0.282 ... Validation loss: 0.447[[ 0.35675219]
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[[ 0.05650115 -0.15225521  0.04066194 ..., -0.14165601  0.17175951
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   0.42243354]
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  -0.23855958]
 [ 0.05993735 -0.03388659 -0.08089784 ...,  0.03757134  0.30617984
   0.1961229 ]]
Progress: 9.4% ... Training loss: 0.293 ... Validation loss: 0.475[[ 0.3477099 ]
 [-0.28681166]
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[[ 0.05679742 -0.15248076  0.04022491 ..., -0.14172422  0.17252334
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 [ 0.04223035  0.04542543  0.1074813  ..., -0.24497292 -0.03206695
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 [ 0.05954369 -0.03355047 -0.07997863 ...,  0.03767243  0.30544966
   0.19715605]]
Progress: 9.4% ... Training loss: 0.277 ... Validation loss: 0.447[[ 0.35089986]
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[[ 0.05627517 -0.15203473  0.04151206 ..., -0.14158023  0.17116496
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  -0.2385904 ]
 [ 0.05976997 -0.03372606 -0.08047893 ...,  0.03761803  0.30606607
   0.19671189]]
Progress: 9.4% ... Training loss: 0.279 ... Validation loss: 0.453[[ 0.34578528]
 [-0.28865803]
 [-0.78501265]
 [-0.80695005]
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 [ 1.38637722]
 [ 0.41152996]
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[[ 0.05605557 -0.15186378  0.04204925 ..., -0.14151488  0.1708207  -0.198146  ]
 [ 0.04199692  0.04560512  0.10797972 ..., -0.2449114  -0.03259296
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 [ 0.05913475 -0.03318353 -0.07912617 ...,  0.03779405  0.3048167
   0.19820937]]
Progress: 9.4% ... Training loss: 0.276 ... Validation loss: 0.448[[ 0.34562535]
 [-0.28892387]
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[[ 0.05656561 -0.15230639  0.0409025  ..., -0.14165865  0.17186307
  -0.19926419]
 [ 0.04203074  0.04557401  0.10787825 ..., -0.24491929 -0.03250425
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  -0.2379613 ]
 [ 0.05919751 -0.03321701 -0.07926134 ...,  0.03778149  0.30492935
   0.1980394 ]]
Progress: 9.4% ... Training loss: 0.277 ... Validation loss: 0.448[[ 0.33682806]
 [-0.29605886]
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 [ 1.37906906]
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[[ 0.05591401 -0.15170483  0.04251104 ..., -0.14146737  0.17034276
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  -0.23815175]
 [ 0.05914298 -0.03315555 -0.07914706 ...,  0.03779531  0.30485005
   0.19810942]]
Progress: 9.4% ... Training loss: 0.294 ... Validation loss: 0.458[[ 0.35024287]
 [-0.28395103]
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 [ 1.38916287]
 [ 0.41420965]
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[[ 0.05714038 -0.15277754  0.03976762 ..., -0.14184709  0.17350125
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 [ 0.04225349  0.04538269  0.1073582  ..., -0.24498132 -0.03195517
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  -0.23856261]
 [ 0.05995287 -0.03385812 -0.08105663 ...,  0.03754646  0.30695338
   0.19624031]]
Progress: 9.4% ... Training loss: 0.279 ... Validation loss: 0.458[[ 0.35936222]
 [-0.27673901]
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 [-0.79622933]
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 [ 1.39920897]
 [ 0.42295837]
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[[ 0.05792332 -0.15342063  0.03804528 ..., -0.14204362  0.17525566
  -0.20220059]
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  -0.23862376]
 [ 0.06051717 -0.034337   -0.08233404 ...,  0.03739209  0.3083819
   0.19489676]]
Progress: 9.4% ... Training loss: 0.306 ... Validation loss: 0.490[[ 0.33971403]
 [-0.29449583]
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[[ 0.05686957 -0.15260552  0.04026208 ..., -0.14178778  0.1731628
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  -0.23705387]
 [ 0.05943298 -0.03346541 -0.0799854  ...,  0.03766239  0.3063471
   0.19744434]]
Progress: 9.4% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.35754748]
 [-0.27982024]
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 [ 1.40405791]
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[[ 0.05873789 -0.15424544  0.0360769  ..., -0.14234815  0.17740103
  -0.20404512]
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   0.19618313]]
Progress: 9.4% ... Training loss: 0.299 ... Validation loss: 0.473[[ 0.3392977 ]
 [-0.29674382]
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 [ 1.39071995]
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[[ 0.05756904 -0.15331175  0.03856952 ..., -0.14206166  0.17471822
  -0.20172535]
 [ 0.04155249  0.04593397  0.10870047 ..., -0.24481364 -0.03349553
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  -0.23529255]
 [ 0.0597576  -0.03376007 -0.08082396 ...,  0.03754884  0.30743336
   0.19659284]]
Progress: 9.4% ... Training loss: 0.287 ... Validation loss: 0.449[[ 0.34514988]
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[[ 0.05822095 -0.15387825  0.03704047 ..., -0.14224302  0.17640368
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 [ 0.04164865  0.04585845  0.10841478 ..., -0.24484449 -0.0332415
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 [ 0.06006559 -0.03401775 -0.08148729 ...,  0.03746397  0.30822832
   0.19575802]]
Progress: 9.4% ... Training loss: 0.276 ... Validation loss: 0.441[[ 0.34889106]
 [-0.28756652]
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[[ 0.05803532 -0.15370901  0.03750167 ..., -0.14218055  0.17609047
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 [-0.19340532 -0.18566747 -0.1178383  ...,  0.10497293 -0.07294335
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  -0.23640182]
 [ 0.05974907 -0.03372874 -0.08077129 ...,  0.03756127  0.30768291
   0.19659813]]
Progress: 9.4% ... Training loss: 0.277 ... Validation loss: 0.447[[ 0.33957648]
 [-0.29592416]
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[[ 0.05683788 -0.15269471  0.04031804 ..., -0.14184218  0.17341158
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 [-0.19372703 -0.18540327 -0.11710481 ...,  0.10505365 -0.07375501
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  -0.23592392]
 [ 0.05940732 -0.03342498 -0.08001312 ...,  0.03765282  0.30721549
   0.19731641]]
Progress: 9.5% ... Training loss: 0.287 ... Validation loss: 0.450[[ 0.35309886]
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[[ 0.0579983  -0.15366934  0.03779151 ..., -0.14218504  0.17591065
  -0.20296578]
 [ 0.04199706  0.04556208  0.10762124 ..., -0.24494229 -0.0323873
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   0.4273606 ]
 ..., 
 [-0.19325392 -0.18580885 -0.11817461 ...,  0.10490499 -0.07269305
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  -0.23611183]
 [ 0.05997009 -0.03393368 -0.08130797 ...,  0.03747585  0.30857557
   0.1959624 ]]
Progress: 9.5% ... Training loss: 0.282 ... Validation loss: 0.457[[ 0.3435433 ]
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[[ 0.05772102 -0.15342689  0.03849652 ..., -0.14211385  0.17537113
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   0.42528718]
 ..., 
 [-0.19321361 -0.1858394  -0.11828653 ...,  0.10489389 -0.07258177
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  -0.23593492]
 [ 0.0596892  -0.03368695 -0.08060749 ...,  0.03755105  0.30801409
   0.19660234]]
Progress: 9.5% ... Training loss: 0.277 ... Validation loss: 0.442[[ 0.33708272]
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[[ 0.05738299 -0.15309687  0.03945727 ..., -0.1420136   0.17476307
  -0.20133772]
 [ 0.04203879  0.0455278   0.10752259 ..., -0.24495101 -0.03228242
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  -0.23630125]
 [ 0.05909416 -0.03314483 -0.07925618 ...,  0.03773892  0.30696692
   0.1980414 ]]
Progress: 9.5% ... Training loss: 0.288 ... Validation loss: 0.449[[ 0.35001506]
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[[ 0.05841677 -0.15401229  0.03714638 ..., -0.1423359   0.17734563
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   0.19760372]]
Progress: 9.5% ... Training loss: 0.278 ... Validation loss: 0.448[[ 0.34289532]
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 [ 1.39781982]
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[[ 0.05708896 -0.15291169  0.04002331 ..., -0.14198584  0.1743173
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   0.1982341 ]]
Progress: 9.5% ... Training loss: 0.279 ... Validation loss: 0.442[[ 0.35392837]
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[[ 0.05797526 -0.15363497  0.03810524 ..., -0.14225055  0.17633816
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  -0.23762926]
 [ 0.05932264 -0.03332512 -0.07982011 ...,  0.03767308  0.30801144
   0.19737766]]
Progress: 9.5% ... Training loss: 0.287 ... Validation loss: 0.452[[ 0.33372535]
 [-0.30248955]
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 [ 1.38773664]
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[[ 0.05585942 -0.15186806  0.04293503 ..., -0.14169124  0.17162842
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  -0.23622903]
 [ 0.05902785 -0.03304698 -0.07913969 ...,  0.03776048  0.30756467
   0.19802322]]
Progress: 9.5% ... Training loss: 0.305 ... Validation loss: 0.466[[ 0.35196349]
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[[ 0.05730675 -0.1531646   0.03965292 ..., -0.14215871  0.17477614
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 [ 0.05857164 -0.03260463 -0.07809159 ...,  0.03791946  0.30660659
   0.19917934]]
Progress: 9.5% ... Training loss: 0.282 ... Validation loss: 0.462[[ 0.33838729]
 [-0.29601567]
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[[ 0.0559181  -0.1519742   0.04275843 ..., -0.14178003  0.1714269
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 [ 0.05747627 -0.0316693  -0.07559639 ...,  0.03822051  0.30446302
   0.201689  ]]
Progress: 9.5% ... Training loss: 0.284 ... Validation loss: 0.451[[ 0.3516663 ]
 [-0.28342983]
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[[ 0.05753931 -0.15334895  0.0392101  ..., -0.14226362  0.17530329
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   0.20110498]]
Progress: 9.5% ... Training loss: 0.287 ... Validation loss: 0.462[[ 0.33252784]
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[[ 0.05591024 -0.15199137  0.04285197 ..., -0.14182677  0.17131576
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   0.20191997]]
Progress: 9.5% ... Training loss: 0.295 ... Validation loss: 0.461[[ 0.35215001]
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[[ 0.05700344 -0.15297977  0.04029636 ..., -0.14217812  0.17398442
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 [ 0.0577514  -0.03187364 -0.07625288 ...,  0.03813207  0.30526148
   0.20092822]]
Progress: 9.5% ... Training loss: 0.293 ... Validation loss: 0.470[[ 0.34724678]
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[[ 0.05643213 -0.15254403  0.04168576 ..., -0.14203116  0.17263457
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  -0.23660808]
 [ 0.05817985 -0.03223294 -0.0771969  ...,  0.03801504  0.30635184
   0.19988714]]
Progress: 9.5% ... Training loss: 0.278 ... Validation loss: 0.455[[ 0.34246276]
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[[ 0.05655716 -0.15260932  0.04144956 ..., -0.14206287  0.17270704
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 [ 0.05872926 -0.03268574 -0.07841738 ...,  0.03786723  0.30766916
   0.19846623]]
Progress: 9.5% ... Training loss: 0.276 ... Validation loss: 0.447[[ 0.3355695 ]
 [-0.29629599]
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[[ 0.05524607 -0.15142068  0.04467346 ..., -0.14166144  0.16941503
  -0.1975417 ]
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  -0.23900751]
 [ 0.05832656 -0.03233057 -0.07757189 ...,  0.03798579  0.30683194
   0.1992652 ]]
Progress: 9.6% ... Training loss: 0.281 ... Validation loss: 0.449[[ 0.33408545]
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[[ 0.05495661 -0.15115407  0.04559011 ..., -0.14157626  0.1686836
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  -0.23882277]
 [ 0.05764435 -0.03170011 -0.07587905 ...,  0.0382008   0.30535766
   0.20086403]]
Progress: 9.6% ... Training loss: 0.286 ... Validation loss: 0.454[[ 0.35301405]
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[[ 0.05586639 -0.15196149  0.04342697 ..., -0.14186118  0.17119959
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  -0.24026867]
 [ 0.05864683 -0.03259035 -0.07824502 ...,  0.03788442  0.30793077
   0.19837422]]
Progress: 9.6% ... Training loss: 0.300 ... Validation loss: 0.472[[ 0.33139686]
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[[ 0.05371525 -0.15021568  0.04809398 ..., -0.14133917  0.16607457
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 [ 0.05817268 -0.03221515 -0.07731986 ...,  0.03800145  0.306934
   0.19944058]]
Progress: 9.6% ... Training loss: 0.295 ... Validation loss: 0.460[[ 0.35133562]
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[[ 0.05478667 -0.15118541  0.0456582  ..., -0.14169432  0.16868222
  -0.19643803]
 [ 0.04244089  0.0451785   0.10648184 ..., -0.24508692 -0.03120784
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  -0.24062245]
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   0.19863437]]
Progress: 9.6% ... Training loss: 0.288 ... Validation loss: 0.465[[ 0.34391992]
 [-0.29008861]
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 [ 1.40171975]
 [ 0.41019739]
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[[ 0.05471657 -0.15114068  0.04592007 ..., -0.1416738   0.16845724
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  -0.24032912]
 [ 0.05823019 -0.03229428 -0.0775072  ...,  0.03797896  0.30729443
   0.19926445]]
Progress: 9.6% ... Training loss: 0.275 ... Validation loss: 0.445[[ 0.34785713]
 [-0.28644677]
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 [ 1.40791583]
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[[ 0.05484148 -0.15126399  0.04570148 ..., -0.1417015   0.16876494
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  -0.24030606]
 [ 0.0585406  -0.0325726  -0.07826486 ...,  0.0378929   0.30810273
   0.19848297]]
Progress: 9.6% ... Training loss: 0.279 ... Validation loss: 0.447[[ 0.34428335]
 [-0.28983496]
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 [ 1.40559138]
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[[ 0.05469714 -0.15113557  0.04603595 ..., -0.1416684   0.16855532
  -0.19642001]
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  -0.23993127]
 [ 0.05815424 -0.03222832 -0.07743139 ...,  0.03800402  0.30734747
   0.19926241]]
Progress: 9.6% ... Training loss: 0.275 ... Validation loss: 0.443[[ 0.33941227]
 [-0.29328502]
 [-0.78403353]
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 [ 1.40091307]
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[[ 0.05454959 -0.15100268  0.04646473 ..., -0.14162911  0.16808161
  -0.1961045 ]
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  -0.24006434]
 [ 0.05822863 -0.03227434 -0.0775448  ...,  0.03799025  0.30759076
   0.19892946]]
Progress: 9.6% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.34453957]
 [-0.28784116]
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 [ 0.41065164]
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[[ 0.05495626 -0.15131934  0.04566369 ..., -0.14174554  0.16866776
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  -0.24001783]
 [ 0.05810691 -0.03213463 -0.07721054 ...,  0.03803898  0.30752323
   0.19921323]]
Progress: 9.6% ... Training loss: 0.276 ... Validation loss: 0.447[[ 0.3463798 ]
 [-0.28587886]
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 [ 1.40560707]
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[[ 0.05555208 -0.15180023  0.04437741 ..., -0.14191478  0.17014703
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  -0.24070317]
 [ 0.05781926 -0.03187263 -0.07655271 ...,  0.03812164  0.30709514
   0.19987988]]
Progress: 9.6% ... Training loss: 0.277 ... Validation loss: 0.450[[ 0.34546451]
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[[ 0.05583034 -0.15199738  0.04393931 ..., -0.14197626  0.17077813
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 [ 0.05818407 -0.03217691 -0.07737156 ...,  0.03802538  0.30801399
   0.19902485]]
Progress: 9.6% ... Training loss: 0.275 ... Validation loss: 0.451[[ 0.33569785]
 [-0.29523664]
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[[ 0.05589368 -0.15203892  0.04390394 ..., -0.14200159  0.17082992
  -0.198396  ]
 [ 0.04250513  0.04513337  0.10630659 ..., -0.24510681 -0.0309271
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 [ 0.05825606 -0.03223358 -0.07754614 ...,  0.03800961  0.30818582
   0.19886367]]
Progress: 9.6% ... Training loss: 0.284 ... Validation loss: 0.450[[ 0.34658718]
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[[ 0.05728628 -0.15326683  0.0407123  ..., -0.14242795  0.17399636
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 [-0.19105903 -0.1878895  -0.12316614 ...,  0.10410758 -0.06831821
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  -0.23989356]
 [ 0.05866784 -0.03260928 -0.07853644 ...,  0.03787889  0.30917828
   0.19791478]]
Progress: 9.6% ... Training loss: 0.278 ... Validation loss: 0.451[[ 0.34115097]
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[[ 0.05695341 -0.15297329  0.04153008 ..., -0.14233517  0.17321314
  -0.20095888]
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 [-0.19107639 -0.18787156 -0.12308079 ...,  0.10411624 -0.0683894
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  -0.23962645]
 [ 0.05869952 -0.03262092 -0.07855696 ...,  0.03787708  0.30937811
   0.19782079]]
Progress: 9.6% ... Training loss: 0.274 ... Validation loss: 0.444[[ 0.34992969]
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[[ 0.05752995 -0.1534013   0.04026229 ..., -0.14248014  0.17452206
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 [ 0.0425714   0.04508784  0.10617276 ..., -0.24512238 -0.03070345
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   0.434896  ]
 ..., 
 [-0.19074748 -0.18814097 -0.12384029 ...,  0.10402616 -0.06774364
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  -0.24145146]
 [ 0.05836974 -0.03232084 -0.07780834 ...,  0.03797408  0.30871054
   0.19861129]]
Progress: 9.7% ... Training loss: 0.290 ... Validation loss: 0.462[[ 0.34350576]
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[[ 0.05706558 -0.15303522  0.04128276 ..., -0.14236057  0.17337167
  -0.20160013]
 [ 0.04254961  0.0451091   0.10620019 ..., -0.24511567 -0.03075659
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 [-0.19088727 -0.1880433  -0.12352708 ...,  0.10405534 -0.06818457
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  -0.24047728]
 [ 0.05820942 -0.03218031 -0.07742804 ...,  0.03801842  0.30847681
   0.19892205]]
Progress: 9.7% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.33295865]
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[[ 0.05602875 -0.15211267  0.04374928 ..., -0.14204364  0.17066875
  -0.19896748]
 [ 0.04273531  0.0449538   0.10577788 ..., -0.24516625 -0.03029111
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 [-0.19113314 -0.18784602 -0.12302117 ...,  0.10412433 -0.06890697
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  -0.24000691]
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   0.19979452]]
Progress: 9.7% ... Training loss: 0.287 ... Validation loss: 0.451[[ 0.35426251]
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[[ 0.05767876 -0.15353508  0.03996264 ..., -0.14255614  0.17456112
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   0.19742933]]
Progress: 9.7% ... Training loss: 0.307 ... Validation loss: 0.481[[ 0.32634224]
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 [ 0.39556523]
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[[ 0.05509756 -0.15144417  0.04557664 ..., -0.141905    0.16852744
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 [ 0.0577255  -0.03182437 -0.07657071 ...,  0.03810289  0.30777829
   0.19987782]]
Progress: 9.7% ... Training loss: 0.310 ... Validation loss: 0.471[[ 0.34206204]
 [-0.28695459]
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 [ 1.40754076]
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[[ 0.05603197 -0.15229882  0.04341263 ..., -0.14221974  0.17082517
  -0.1992852 ]
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 [ 0.05805803 -0.03212018 -0.07735141 ...,  0.037988    0.30878421
   0.19895326]]
Progress: 9.7% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.33177057]
 [-0.29604927]
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[[ 0.05495254 -0.15139348  0.04583775 ..., -0.14192042  0.16843428
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 [ 0.04269058  0.04496712  0.10581638 ..., -0.24516772 -0.03046773
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  -0.23948925]
 [ 0.05695341 -0.03114326 -0.07485669 ...,  0.03831961  0.306416
   0.20145633]]
Progress: 9.7% ... Training loss: 0.287 ... Validation loss: 0.453[[ 0.34624667]
 [-0.28295449]
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 [ 1.41072724]
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[[ 0.05566258 -0.15206687  0.04421512 ..., -0.14215576  0.17028714
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  -0.23954098]
 [ 0.05702927 -0.0312155  -0.07504579 ...,  0.03829885  0.30664645
   0.20132518]]
Progress: 9.7% ... Training loss: 0.281 ... Validation loss: 0.455[[ 0.33451212]
 [-0.29310698]
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[[ 0.05510669 -0.15159256  0.04544752 ..., -0.14200452  0.16895996
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  -0.23983719]
 [ 0.05663391 -0.03087468 -0.0741689  ...,  0.03841791  0.30573127
   0.2021059 ]]
Progress: 9.7% ... Training loss: 0.282 ... Validation loss: 0.452[[ 0.34832227]
 [-0.28111898]
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[[ 0.05583887 -0.15221666  0.04376326 ..., -0.14223091  0.17088707
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 [ 0.05699506 -0.03117324 -0.07500525 ...,  0.03831344  0.30675696
   0.20126531]]
Progress: 9.7% ... Training loss: 0.287 ... Validation loss: 0.464[[ 0.33137779]
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[[ 0.05489098 -0.15140899  0.0460115  ..., -0.14196535  0.1685788
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 [ 0.0432752   0.04445802  0.10437692 ..., -0.24534293 -0.02901078
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   0.20191901]]
Progress: 9.7% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.34625225]
 [-0.28219638]
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[[ 0.05597619 -0.15235045  0.04353959 ..., -0.1422928   0.17138581
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  -0.24119594]
 [ 0.05688049 -0.03107612 -0.0747621  ...,  0.03833871  0.30680589
   0.20144637]]
Progress: 9.7% ... Training loss: 0.287 ... Validation loss: 0.457[[ 0.33879273]
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[[ 0.05512237 -0.15165796  0.04547332 ..., -0.14206596  0.16922302
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 [-0.19144952 -0.18772687 -0.1223446  ...,  0.10410449 -0.06990752
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 [ 0.05745283 -0.03154585 -0.07607045 ...,  0.03819051  0.30823893
   0.2001124 ]]
Progress: 9.7% ... Training loss: 0.274 ... Validation loss: 0.442[[ 0.34034563]
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[[ 0.05558767 -0.15201814  0.0444849  ..., -0.14220614  0.17001453
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 [ 0.05780715 -0.03185622 -0.07687244 ...,  0.0380916   0.30912225
   0.19927061]]
Progress: 9.7% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.33196834]
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[[ 0.05496691 -0.1514802   0.04597784 ..., -0.1420323   0.16868111
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  -0.240788  ]
 [ 0.05704239 -0.03117747 -0.07520339 ...,  0.03831216  0.30747542
   0.20100581]]
Progress: 9.7% ... Training loss: 0.282 ... Validation loss: 0.449[[ 0.34619283]
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[[ 0.05603053 -0.15245899  0.04365693 ..., -0.14235913  0.17134067
  -0.19937084]
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 [-0.19107016 -0.18806586 -0.12325118 ...,  0.10396678 -0.06917863
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  -0.24117228]
 [ 0.05762448 -0.03171451 -0.07657876 ...,  0.03812865  0.30916806
   0.19944251]]
Progress: 9.8% ... Training loss: 0.282 ... Validation loss: 0.447[[ 0.32913578]
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[[ 0.05398701 -0.1507729   0.04840716 ..., -0.14181374  0.16648504
  -0.1949173 ]
 [ 0.04273156  0.04493734  0.10558684 ..., -0.24520308 -0.03017453
   0.11206094]
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   0.44203961]
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 [-0.19143631 -0.1877706  -0.12244006 ...,  0.10405547 -0.07001821
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  -0.24090501]
 [ 0.05670301 -0.03092949 -0.07447966 ...,  0.03838146  0.3071579
   0.20165251]]
Progress: 9.8% ... Training loss: 0.294 ... Validation loss: 0.461[[ 0.34448887]
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[[ 0.05456436 -0.15130121  0.04714429 ..., -0.14201128  0.16798439
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 [ 0.0429134   0.04477592  0.10517215 ..., -0.24526179 -0.02969903
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 [-0.19124071 -0.18795048 -0.1228247  ...,  0.10398558 -0.0696142
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 [ 0.05667462 -0.03089241 -0.0744321  ...,  0.03838769  0.30717072
   0.20150162]]
Progress: 9.8% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.33975528]
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[[ 0.05462037 -0.15130826  0.04710236 ..., -0.14201217  0.16791582
  -0.1964609 ]
 [ 0.04300316  0.04470706  0.10491899 ..., -0.2452837  -0.02949053
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  -0.24128497]
 [ 0.05667824 -0.03085624 -0.07447295 ...,  0.03838684  0.30750097
   0.20162155]]
Progress: 9.8% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.33437223]
 [-0.28906205]
 [-0.78330825]
 [-0.80960889]
 [-0.22477861]
 [ 1.41466808]
 [ 0.4077959 ]
 [-0.6245262 ]
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[[ 0.05477181 -0.15138693  0.04682628 ..., -0.14204322  0.16841281
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  -0.24089286]
 [ 0.05679059 -0.03092112 -0.07481724 ...,  0.03836509  0.30812946
   0.20116985]]
Progress: 9.8% ... Training loss: 0.277 ... Validation loss: 0.442[[ 0.33628027]
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[[ 0.05508662 -0.15165015  0.04616183 ..., -0.14213878  0.16927569
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  -0.24021893]
 [ 0.05667381 -0.03081917 -0.07446153 ...,  0.03839311  0.30801806
   0.20152909]]
Progress: 9.8% ... Training loss: 0.276 ... Validation loss: 0.440[[ 0.34150957]
 [-0.28419892]
 [-0.77972611]
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 [ 1.42269166]
 [ 0.41486773]
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[[ 0.05545533 -0.15199595  0.04540066 ..., -0.1422615   0.17015716
  -0.19841289]
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  -0.24012301]
 [ 0.0569037  -0.0310151  -0.07497318 ...,  0.03832465  0.30867906
   0.20095659]]
Progress: 9.8% ... Training loss: 0.278 ... Validation loss: 0.439[[ 0.33027215]
 [-0.29413   ]
 [-0.78794247]
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 [ 1.41452822]
 [ 0.40466794]
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[[ 0.05412688 -0.15088686  0.04850183 ..., -0.14191186  0.16707959
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  -0.2401211 ]
 [ 0.05648646 -0.03065594 -0.07402468 ...,  0.03843868  0.30784946
   0.20192532]]
Progress: 9.8% ... Training loss: 0.286 ... Validation loss: 0.454[[ 0.34097683]
 [-0.28368692]
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[[ 0.054758   -0.15146298  0.04714724 ..., -0.14210406  0.16849912
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 [ 0.04326552  0.04449287  0.10429578 ..., -0.2453568  -0.02876698
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 [ 0.05694141 -0.03107584 -0.07509373 ...,  0.03829361  0.30888749
   0.2007904 ]]
Progress: 9.8% ... Training loss: 0.276 ... Validation loss: 0.443[[ 0.33944386]
 [-0.285868  ]
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 [ 1.41466589]
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[[ 0.05496021 -0.15161533  0.04679645 ..., -0.14216374  0.16887088
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 [ 0.04324493  0.04450962  0.10433984 ..., -0.24535074 -0.02882009
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  -0.24102853]
 [ 0.05683839 -0.03098035 -0.0748843  ...,  0.03831785  0.30877235
   0.2010147 ]]
Progress: 9.8% ... Training loss: 0.275 ... Validation loss: 0.442[[ 0.34418014]
 [-0.28126538]
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[[ 0.05504908 -0.15159935  0.04670522 ..., -0.14214034  0.1690845
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  -0.24102943]
 [ 0.05705006 -0.03113347 -0.07533038 ...,  0.03827086  0.3093945
   0.20035138]]
Progress: 9.8% ... Training loss: 0.282 ... Validation loss: 0.444[[ 0.32359102]
 [-0.2982483 ]
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[[ 0.05294121 -0.14976473  0.0517046  ..., -0.1415581   0.16410522
  -0.19284863]
 [ 0.04320483  0.04454857  0.10440724 ..., -0.24533971 -0.02891656
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 [ 0.05657188 -0.03072542 -0.07430406 ...,  0.03839718  0.30837788
   0.20126346]]
Progress: 9.8% ... Training loss: 0.303 ... Validation loss: 0.479[[ 0.34314995]
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[[ 0.0538874  -0.15068644  0.04945635 ..., -0.14186869  0.16644501
  -0.19512259]
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 [-0.19038927 -0.18870279 -0.12464565 ...,  0.10371138 -0.06773893
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  -0.24134613]
 [ 0.05744364 -0.03155656 -0.07646536 ...,  0.03811307  0.31048589
   0.19898301]]
Progress: 9.8% ... Training loss: 0.280 ... Validation loss: 0.442[[ 0.34157729]
 [-0.28326212]
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[[ 0.05408837 -0.15086165  0.04902966 ..., -0.14190607  0.16689372
  -0.19562623]
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 [-0.19015021 -0.18891372 -0.12517361 ...,  0.10365153 -0.06728078
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  -0.24127266]
 [ 0.05758811 -0.03168038 -0.07681214 ...,  0.03806572  0.31118297
   0.19850609]]
Progress: 9.8% ... Training loss: 0.279 ... Validation loss: 0.439[[ 0.3426166 ]
 [-0.28325694]
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[[ 0.05531377 -0.15193392  0.04627606 ..., -0.14223528  0.16984733
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   0.11010452]
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 ..., 
 [-0.1902085  -0.18887566 -0.1249911  ...,  0.10366845 -0.06746728
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  -0.24064457]
 [ 0.05804508 -0.03206183 -0.07782497 ...,  0.03795595  0.31234638
   0.19745433]]
Progress: 9.8% ... Training loss: 0.279 ... Validation loss: 0.439[[ 0.33146631]
 [-0.29322657]
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[[ 0.05436322 -0.15113751  0.04853146 ..., -0.1419813   0.16750854
  -0.19616142]
 [ 0.04301512  0.04470211  0.104846   ..., -0.24529796 -0.0293164
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 ..., 
 [-0.19064611 -0.18851614 -0.12414236 ...,  0.10378584 -0.06840505
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  -0.24015552]
 [ 0.05817027 -0.03216    -0.07818382 ...,  0.0379253   0.31277793
   0.19716556]]
Progress: 9.9% ... Training loss: 0.282 ... Validation loss: 0.451[[ 0.33758043]
 [-0.28789399]
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[[ 0.05399512 -0.15082357  0.04950059 ..., -0.14186567  0.16685942
  -0.19526288]
 [ 0.04277442  0.0449169   0.10540428 ..., -0.24523179 -0.02976529
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 [-0.19082684 -0.18835563 -0.12370455 ...,  0.10384297 -0.06888868
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  -0.24047091]
 [ 0.05834054 -0.03230098 -0.07854464 ...,  0.0378837   0.31325368
   0.19668689]]
Progress: 9.9% ... Training loss: 0.275 ... Validation loss: 0.444[[ 0.34225145]
 [-0.28424568]
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 [ 1.41699533]
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[[ 0.05479355 -0.15153435  0.04768978 ..., -0.14208942  0.16864523
  -0.19742776]
 [ 0.04271725  0.04496545  0.10553529 ..., -0.24521336 -0.02991335
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 [-0.19101171 -0.18820063 -0.12328861 ...,  0.10389321 -0.06935578
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 [ 0.0586683  -0.03259686 -0.07929838 ...,  0.03778253  0.31405872
   0.1958309 ]]
Progress: 9.9% ... Training loss: 0.275 ... Validation loss: 0.443[[ 0.33772854]
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[[ 0.05477    -0.15145866  0.04789566 ..., -0.14207614  0.16856286
  -0.19732363]
 [ 0.04240257  0.04523756  0.10625083 ..., -0.24513193 -0.03068176
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  -0.24118167]
 [ 0.05811801 -0.03205766 -0.07804296 ...,  0.03796321  0.31307238
   0.19690086]]
Progress: 9.9% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.33661972]
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[[ 0.05401167 -0.15084444  0.04964332 ..., -0.14187045  0.16682345
  -0.19553917]
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   0.19644675]]
Progress: 9.9% ... Training loss: 0.277 ... Validation loss: 0.446[[ 0.33807489]
 [-0.28994223]
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[[ 0.0546622  -0.15138905  0.04819693 ..., -0.14205452  0.16853127
  -0.19709306]
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  -0.2415753 ]
 [ 0.05918332 -0.03299356 -0.08058116 ...,  0.03764654  0.31578794
   0.19419671]]
Progress: 9.9% ... Training loss: 0.274 ... Validation loss: 0.442[[ 0.33468483]
 [-0.29275486]
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 [-0.80974042]
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 [ 1.414224  ]
 [ 0.40503915]
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[[ 0.05496972 -0.15164762  0.04760589 ..., -0.14213799  0.16928727
  -0.19757059]
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  -0.24165871]
 [ 0.0589425  -0.03275886 -0.08013355 ...,  0.03772739  0.31531794
   0.19478097]]
Progress: 9.9% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.34742002]
 [-0.28209913]
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 [ 1.42250739]
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[[ 0.05609503 -0.15268645  0.04514582 ..., -0.14248708  0.17190813
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  -0.2413531 ]
 [ 0.05986485 -0.03356613 -0.0822423  ...,  0.03745729  0.31761534
   0.19258461]]
Progress: 9.9% ... Training loss: 0.282 ... Validation loss: 0.454[[ 0.33084022]
 [-0.295997  ]
 [-0.7907923 ]
 [-0.81369531]
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 [ 1.41537297]
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[[ 0.05506595 -0.15181916  0.0475665  ..., -0.14221441  0.16933682
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  -0.24113877]
 [ 0.05961537 -0.0333615  -0.08169583 ...,  0.03752198  0.31710528
   0.1930443 ]]
Progress: 9.9% ... Training loss: 0.287 ... Validation loss: 0.453[[ 0.34033421]
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[[ 0.0557898  -0.15248237  0.04600958 ..., -0.14242921  0.17114709
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 [ 0.05995742 -0.03368488 -0.08250329 ...,  0.03741672  0.31796062
   0.19220369]]
Progress: 9.9% ... Training loss: 0.274 ... Validation loss: 0.440[[ 0.35283216]
 [-0.27921237]
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[[ 0.05711108 -0.15364283  0.0429272  ..., -0.14279723  0.17426841
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   0.19163846]]
Progress: 9.9% ... Training loss: 0.301 ... Validation loss: 0.461[[ 0.33449264]
 [-0.29596267]
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[[ 0.05601997 -0.15277581  0.04539168 ..., -0.14253603  0.17167618
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 [ 0.04283634  0.04482357  0.10522373 ..., -0.24527425 -0.02941485
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 [-0.19153644 -0.18774424 -0.12207393 ...,  0.10404246 -0.07069711
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 [ 0.05978987 -0.03354762 -0.08230372 ...,  0.0374515   0.31790843
   0.19241486]]
Progress: 9.9% ... Training loss: 0.281 ... Validation loss: 0.447[[ 0.33857352]
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[[ 0.05624349 -0.15300106  0.04483692 ..., -0.14257824  0.17236881
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 [ 0.05988303 -0.03364628 -0.08260139 ...,  0.0374189   0.31826405
   0.19220365]]
Progress: 9.9% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.34085071]
 [-0.28972236]
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[[ 0.0567325  -0.15338395  0.04377189 ..., -0.14269347  0.17365234
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 [-0.19147593 -0.18779579 -0.12222934 ...,  0.10402584 -0.07057044
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 [ 0.05958241 -0.03336333 -0.08199715 ...,  0.0375151   0.31777954
   0.19292621]]
Progress: 9.9% ... Training loss: 0.274 ... Validation loss: 0.438[[ 0.33630652]
 [-0.29315424]
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[[ 0.05576572 -0.1525493   0.04605634 ..., -0.14242441  0.17117522
  -0.19945638]
 [ 0.04275059  0.04490792  0.10542985 ..., -0.24524207 -0.02949964
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 [-0.19213644 -0.18723822 -0.12072655 ...,  0.10420341 -0.07220812
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  -0.23958721]
 [ 0.05929242 -0.03310588 -0.08138531 ...,  0.03759256  0.31728677
   0.19350188]]
Progress: 9.9% ... Training loss: 0.278 ... Validation loss: 0.441[[ 0.34714852]
 [-0.28371271]
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[[ 0.05658914 -0.15326931  0.04420073 ..., -0.14265972  0.17296289
  -0.20107414]
 [ 0.04283096  0.04483729  0.10524245 ..., -0.24526493 -0.02928762
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 [-0.19195235 -0.18738901 -0.12111232 ...,  0.10415534 -0.07173338
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  -0.24021275]
 [ 0.05982163 -0.03357725 -0.08262931 ...,  0.03743745  0.3186335
   0.19217239]]
Progress: 10.0% ... Training loss: 0.282 ... Validation loss: 0.444[[ 0.34511348]
 [-0.28613843]
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[[ 0.05674684 -0.15338917  0.04402448 ..., -0.14269867  0.17304331
  -0.20150194]
 [ 0.04281513  0.04484983  0.10527926 ..., -0.24526069 -0.02932905
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 [-0.19204424 -0.18731617 -0.1208183  ...,  0.10417524 -0.07201885
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  -0.23996246]
 [ 0.05999615 -0.03371907 -0.08301404 ...,  0.03739302  0.31903934
   0.19182806]]
Progress: 10.0% ... Training loss: 0.277 ... Validation loss: 0.441[[ 0.33994042]
 [-0.29044038]
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[[ 0.05548401 -0.15230003  0.04689532 ..., -0.14236585  0.17016128
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 [ 0.05973433 -0.03347671 -0.0823373  ...,  0.03746921  0.31869019
   0.1924622 ]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.440[[ 0.34217473]
 [-0.28926882]
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 [-0.80460569]
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 [ 1.42256112]
 [ 0.41186   ]
 [-0.62125184]
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[[ 0.05591646 -0.15268482  0.04609721 ..., -0.14248326  0.17094644
  -0.1992138 ]
 [ 0.04282597  0.04484063  0.10524617 ..., -0.24526241 -0.02931026
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  -0.2399272 ]
 [ 0.05957964 -0.03333122 -0.08194294 ...,  0.0375167   0.31850407
   0.19295503]]
Progress: 10.0% ... Training loss: 0.276 ... Validation loss: 0.444[[ 0.34130482]
 [-0.2909284 ]
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[[ 0.05627367 -0.15303246  0.04519235 ..., -0.14260296  0.17196955
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  -0.23981785]
 [ 0.05887815 -0.03269965 -0.08035806 ...,  0.03772429  0.3171158
   0.19470218]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.440[[ 0.34725871]
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[[ 0.05762741 -0.15416409  0.0422486  ..., -0.14297125  0.1750519
  -0.20304594]
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  -0.24072531]
 [ 0.05954579 -0.03326941 -0.08187047 ...,  0.03754402  0.3189716
   0.19330505]]
Progress: 10.0% ... Training loss: 0.283 ... Validation loss: 0.451[[ 0.33745166]
 [-0.29361258]
 [-0.78912693]
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 [ 1.42444419]
 [ 0.40706282]
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[[ 0.05690541 -0.15357081  0.04399308 ..., -0.14278708  0.17294433
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  -0.24013538]
 [ 0.05971894 -0.03339174 -0.08216579 ...,  0.03750135  0.31935762
   0.19279344]]
Progress: 10.0% ... Training loss: 0.277 ... Validation loss: 0.441[[ 0.33134104]
 [-0.29863994]
 [-0.79417139]
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 [ 1.41864991]
 [ 0.40258231]
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[[ 0.05554964 -0.15234789  0.04730765 ..., -0.14238762  0.17000233
  -0.19826042]
 [ 0.04282838  0.04484     0.10520918 ..., -0.24526475 -0.02930813
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  -0.24020467]
 [ 0.05894698 -0.03267897 -0.08029637 ...,  0.03774047  0.31784722
   0.19461838]]
Progress: 10.0% ... Training loss: 0.292 ... Validation loss: 0.452[[ 0.33778091]
 [-0.2925908 ]
 [-0.786026  ]
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 [ 1.42816864]
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[[ 0.05667313 -0.15335375  0.04469963 ..., -0.14274843  0.17328826
  -0.20077402]
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 [ 0.05888759 -0.03260377 -0.08037572 ...,  0.03775472  0.31801673
   0.19463164]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.438[[ 0.33827737]
 [-0.29171204]
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[[ 0.05661559 -0.15329016  0.04482836 ..., -0.14273591  0.17308832
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 ..., 
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   0.19367902]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.439[[ 0.3379059 ]
 [-0.29129154]
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[[ 0.05628069 -0.15294876  0.04574324 ..., -0.1426172   0.17210955
  -0.19993252]
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  -0.24139206]
 [ 0.05943799 -0.03306256 -0.08160409 ...,  0.03760488  0.31932349
   0.19308355]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.33677234]
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[[ 0.05586294 -0.15259053  0.04677976 ..., -0.14251308  0.17122482
  -0.19858582]
 [ 0.04270566  0.0449292   0.10546825 ..., -0.24524044 -0.02938856
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  -0.24163144]
 [ 0.05959763 -0.03320235 -0.08196441 ...,  0.03756023  0.31975458
   0.19282072]]
Progress: 10.0% ... Training loss: 0.276 ... Validation loss: 0.442[[ 0.34773324]
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[[ 0.05652517 -0.15317304  0.04537489 ..., -0.14271891  0.17309294
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 [-0.19172308 -0.18765916 -0.12139313 ...,  0.10408104 -0.07142381
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  -0.24267977]
 [ 0.05988522 -0.03345213 -0.08271605 ...,  0.03747939  0.32055454
   0.19195843]]
Progress: 10.0% ... Training loss: 0.283 ... Validation loss: 0.456[[ 0.33671031]
 [-0.29334569]
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[[ 0.05629849 -0.15299767  0.04587123 ..., -0.14266379  0.17259329
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 [ 0.04290442  0.04476739  0.10503974 ..., -0.24528641 -0.02886405
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  -0.0401008 ]
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  -0.24191255]
 [ 0.05965871 -0.0332408  -0.08226156 ...,  0.03754483  0.32008362
   0.19236507]]
Progress: 10.0% ... Training loss: 0.275 ... Validation loss: 0.442[[ 0.33444315]
 [-0.29533601]
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[[ 0.05600455 -0.15271379  0.04669979 ..., -0.14255878  0.17170868
  -0.19916932]
 [ 0.04285746  0.04480738  0.10514216 ..., -0.24527266 -0.02894642
   0.11186295]
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   0.45575284]
 ..., 
 [-0.19166856 -0.18771575 -0.12149414 ...,  0.1040643  -0.07145405
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  -0.24118313]
 [ 0.05904285 -0.03265501 -0.08073478 ...,  0.03772992  0.3187217
   0.19393282]]
Progress: 10.0% ... Training loss: 0.279 ... Validation loss: 0.447[[ 0.33910602]
 [-0.29114978]
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[[ 0.05589733 -0.15259711  0.04701242 ..., -0.14251695  0.17160605
  -0.19857764]
 [ 0.04285198  0.04481222  0.10515424 ..., -0.24527102 -0.02895931
   0.11187666]
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 ..., 
 [-0.19159839 -0.18777831 -0.12167615 ...,  0.10404693 -0.07134856
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  -0.24137408]
 [ 0.05936888 -0.03294398 -0.08151809 ...,  0.03764069  0.31969665
   0.19323065]]
Progress: 10.1% ... Training loss: 0.274 ... Validation loss: 0.441[[ 0.33892006]
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[[ 0.05562804 -0.15236103  0.04768414 ..., -0.14244344  0.17080685
  -0.19795247]
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   0.19320998]]
Progress: 10.1% ... Training loss: 0.275 ... Validation loss: 0.443[[ 0.33848627]
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[[ 0.05447844 -0.15136045  0.05034577 ..., -0.14212866  0.16794145
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 [ 0.05939945 -0.0329663  -0.08164343 ...,  0.03763332  0.31981442
   0.19307206]]
Progress: 10.1% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.34524703]
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 [ 0.41108572]
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[[ 0.0557025  -0.15240294  0.04767504 ..., -0.14247154  0.17083897
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   0.19121551]]
Progress: 10.1% ... Training loss: 0.276 ... Validation loss: 0.448[[ 0.33740369]
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[[ 0.05503115 -0.15184824  0.04920572 ..., -0.14228837  0.16921318
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   0.19136052]]
Progress: 10.1% ... Training loss: 0.278 ... Validation loss: 0.444[[ 0.34449019]
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[[ 0.05546127 -0.15220149  0.0481771  ..., -0.14240178  0.17032342
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  -0.24108753]
 [ 0.06026548 -0.03369006 -0.08363339 ...,  0.03739923  0.32243425
   0.190943  ]]
Progress: 10.1% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.34286494]
 [-0.29200521]
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[[ 0.05563419 -0.15232128  0.04781458 ..., -0.1424316   0.17077166
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  -0.24091144]
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   0.19123754]]
Progress: 10.1% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.34552662]
 [-0.29052894]
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[[ 0.05649706 -0.15303398  0.04593617 ..., -0.14266005  0.17292853
  -0.20014873]
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   0.1922639 ]]
Progress: 10.1% ... Training loss: 0.275 ... Validation loss: 0.444[[ 0.35435818]
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[[ 0.05752511 -0.15393767  0.04360319 ..., -0.14292998  0.17550083
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   0.19094127]]
Progress: 10.1% ... Training loss: 0.292 ... Validation loss: 0.466[[ 0.33531341]
 [-0.30137096]
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[[ 0.05681115 -0.1533576   0.04519278 ..., -0.14276391  0.17365808
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 [ 0.05942065 -0.03293162 -0.08166891 ...,  0.03763062  0.32113314
   0.19285883]]
Progress: 10.1% ... Training loss: 0.286 ... Validation loss: 0.445[[ 0.34628113]
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[[ 0.05712426 -0.15361178  0.04451442 ..., -0.14283916  0.17451674
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  -0.24079397]
 [ 0.05997257 -0.03341201 -0.08289961 ...,  0.03747331  0.3224771
   0.19155177]]
Progress: 10.1% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.34587782]
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[[ 0.05709733 -0.15355392  0.04469568 ..., -0.1428291   0.17451869
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 [ 0.06013406 -0.03352721 -0.08325679 ...,  0.03743874  0.32285636
   0.19118002]]
Progress: 10.1% ... Training loss: 0.274 ... Validation loss: 0.445[[ 0.33345353]
 [-0.30255792]
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[[ 0.05565574 -0.15234111  0.04800363 ..., -0.14246352  0.17116169
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  -0.23965617]
 [ 0.05973032 -0.03318844 -0.08234484 ...,  0.03754126  0.32213905
   0.19205845]]
Progress: 10.1% ... Training loss: 0.289 ... Validation loss: 0.452[[ 0.34985299]
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[[ 0.05690472 -0.15352145  0.0449525  ..., -0.14285633  0.17415499
  -0.20121524]
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 [-0.19130821 -0.18810242 -0.1223067  ...,  0.10393017 -0.07124593
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  -0.23996692]
 [ 0.06028938 -0.03367749 -0.08366404 ...,  0.03737871  0.32357977
   0.19061876]]
Progress: 10.1% ... Training loss: 0.281 ... Validation loss: 0.456[[ 0.34982422]
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[[ 0.05725821 -0.15379747  0.04424621 ..., -0.14296091  0.17491582
  -0.20188308]
 [ 0.04353679  0.04421927  0.10359874 ..., -0.2454694  -0.02705725
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 [-0.19090177 -0.18844764 -0.12315896 ...,  0.10382762 -0.07039097
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  -0.23931009]
 [ 0.0603176  -0.03368957 -0.08373439 ...,  0.03736639  0.32379713
   0.19054264]]
Progress: 10.1% ... Training loss: 0.280 ... Validation loss: 0.457[[ 0.34095105]
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[[ 0.05636785 -0.15304278  0.04624525 ..., -0.14274677  0.1728472
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 [-0.19086165 -0.18847892 -0.12321168 ...,  0.10381568 -0.07027619
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  -0.23858869]
 [ 0.06007363 -0.03345425 -0.08321272 ...,  0.03743512  0.32344674
   0.19118295]]
Progress: 10.2% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.35527662]
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[[ 0.0573861  -0.15392938  0.04386312 ..., -0.14304492  0.17545896
  -0.2023434 ]
 [ 0.04358088  0.04418378  0.10343758 ..., -0.24548218 -0.02687008
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 [-0.19053393 -0.18875256 -0.12391371 ...,  0.10371737 -0.06954761
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   0.18991744]]
Progress: 10.2% ... Training loss: 0.295 ... Validation loss: 0.473[[ 0.34134787]
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[[ 0.05625575 -0.15300352  0.04634046 ..., -0.14277106  0.17291494
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   0.18976185]]
Progress: 10.2% ... Training loss: 0.274 ... Validation loss: 0.439[[ 0.33203135]
 [-0.30468398]
 [-0.79508128]
 [-0.81488454]
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 [ 1.42219833]
 [ 0.39600299]
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[[ 0.05495707 -0.15181821  0.04941151 ..., -0.14238224  0.16955825
  -0.19697414]
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   0.18982546]]
Progress: 10.2% ... Training loss: 0.299 ... Validation loss: 0.457[[ 0.34301963]
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 [ 0.40551058]
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[[ 0.05570805 -0.15253856  0.04768003 ..., -0.14261668  0.17140491
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  -0.23923982]
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   0.1894755 ]]
Progress: 10.2% ... Training loss: 0.273 ... Validation loss: 0.443[[ 0.34398035]
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 [ 1.42810562]
 [ 0.40600205]
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[[ 0.05544771 -0.15228765  0.04840158 ..., -0.14255309  0.17082631
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  -0.23894486]
 [ 0.06053572 -0.0337988  -0.08432229 ...,  0.03731333  0.32507277
   0.18981453]]
Progress: 10.2% ... Training loss: 0.273 ... Validation loss: 0.446[[ 0.34646493]
 [-0.29251852]
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 [ 1.43108258]
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[[ 0.05591642 -0.15268375  0.04751947 ..., -0.14267794  0.17183599
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  -0.23909058]
 [ 0.06043108 -0.03370762 -0.08406848 ...,  0.03734956  0.32502046
   0.19000019]]
Progress: 10.2% ... Training loss: 0.273 ... Validation loss: 0.448[[ 0.338846  ]
 [-0.29875055]
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 [ 1.42901304]
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[[ 0.05587791 -0.15265827  0.04753872 ..., -0.14267435  0.17177185
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  -0.23801822]
 [ 0.05986988 -0.03319798 -0.08279897 ...,  0.03750706  0.32381745
   0.1913089 ]]
Progress: 10.2% ... Training loss: 0.276 ... Validation loss: 0.444[[ 0.33812368]
 [-0.30102631]
 [-0.79033193]
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 [ 1.42986035]
 [ 0.39894683]
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[[ 0.05620238 -0.15295206  0.04681772 ..., -0.14277639  0.17273651
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  -0.23828777]
 [ 0.0592562  -0.03264185 -0.08146436 ...,  0.03768762  0.32264458
   0.19283904]]
Progress: 10.2% ... Training loss: 0.278 ... Validation loss: 0.446[[ 0.341287  ]
 [-0.29789522]
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 [ 1.43040748]
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[[ 0.05579468 -0.15258543  0.04778256 ..., -0.14265575  0.17176681
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   0.19214148]]
Progress: 10.2% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.34962794]
 [-0.29090978]
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[[ 0.05665062 -0.15334114  0.04582487 ..., -0.14290044  0.17394548
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   0.19194246]]
Progress: 10.2% ... Training loss: 0.277 ... Validation loss: 0.447[[ 0.33046703]
 [-0.30785234]
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[[ 0.05512563 -0.15198956  0.04927726 ..., -0.14250637  0.17040677
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 [-0.19059702 -0.18879565 -0.1237572  ...,  0.10366705 -0.07005808
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  -0.23819851]
 [ 0.05889083 -0.03230015 -0.08076552 ...,  0.03778413  0.32195626
   0.19340276]]
Progress: 10.2% ... Training loss: 0.304 ... Validation loss: 0.471[[ 0.34489295]
 [-0.29430023]
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[[ 0.05556758 -0.15242046  0.04828579 ..., -0.14264292  0.17151617
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 [-0.19028955 -0.18908181 -0.12449677 ...,  0.1035701  -0.06928464
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  -0.23905293]
 [ 0.0592927  -0.03266228 -0.08165873 ...,  0.03766617  0.32297029
   0.19249908]]
Progress: 10.2% ... Training loss: 0.273 ... Validation loss: 0.444[[ 0.35220921]
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[[ 0.05616653 -0.15295118  0.0469805  ..., -0.1427997   0.17279337
  -0.19976585]
 [ 0.0431547   0.04450237  0.1041181  ..., -0.2453979  -0.0274276
   0.11114701]
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 [-0.19011937 -0.18922726 -0.12486468 ...,  0.10352681 -0.06894854
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  -0.23873636]
 [ 0.05921173 -0.03259543 -0.08149668 ...,  0.03768979  0.32274849
   0.19267063]]
Progress: 10.2% ... Training loss: 0.284 ... Validation loss: 0.455[[ 0.33720546]
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[[ 0.05527561 -0.15219472  0.04896694 ..., -0.14256903  0.17069217
  -0.19778955]
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 [-0.19122513 -0.18832807 -0.12245635 ...,  0.10379553 -0.07165558
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  -0.23804321]
 [ 0.05838502 -0.0318799  -0.07969732 ...,  0.03790244  0.32106708
   0.19467058]]
Progress: 10.2% ... Training loss: 0.281 ... Validation loss: 0.450[[ 0.34341596]
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[[ 0.05494853 -0.15192671  0.04976408 ..., -0.14246388  0.16996941
  -0.19679821]
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 ..., 
 [-0.19104477 -0.1884879  -0.12284771 ...,  0.1037481  -0.07116758
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  -0.23834732]
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   0.19431239]]
Progress: 10.3% ... Training loss: 0.273 ... Validation loss: 0.445[[ 0.35151788]
 [-0.28972802]
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[[ 0.05515881 -0.15211297  0.04931111 ..., -0.14253816  0.17048072
  -0.19734567]
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   0.19388335]]
Progress: 10.3% ... Training loss: 0.279 ... Validation loss: 0.450[[ 0.34053278]
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[[ 0.05423977 -0.15135875  0.05129398 ..., -0.1423148   0.1684849
  -0.19543003]
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 [-0.19152319 -0.18811094 -0.12178471 ...,  0.10386784 -0.072244
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  -0.23899144]
 [ 0.05803449 -0.03157176 -0.07903281 ...,  0.03798891  0.32082647
   0.19541736]]
Progress: 10.3% ... Training loss: 0.278 ... Validation loss: 0.450[[ 0.35178786]
 [-0.29024432]
 [-0.77934765]
 [-0.79679763]
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 [ 1.43618261]
 [ 0.40892306]
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[[ 0.0552591  -0.15228703  0.04896106 ..., -0.14261645  0.17111179
  -0.19792283]
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 [-0.19115512 -0.18843638 -0.1226524  ...,  0.10376633 -0.07140332
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  -0.23943314]
 [ 0.05840482 -0.03190454 -0.07986495 ...,  0.03788327  0.32177023
   0.19452428]]
Progress: 10.3% ... Training loss: 0.279 ... Validation loss: 0.452[[ 0.34012637]
 [-0.30074269]
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 [ 0.39862546]
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[[ 0.05456141 -0.15173002  0.05077189 ..., -0.1424366   0.16952954
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  -0.23982415]
 [ 0.05810034 -0.03165389 -0.07917048 ...,  0.03796126  0.32128909
   0.19530085]]
Progress: 10.3% ... Training loss: 0.280 ... Validation loss: 0.453[[ 0.34910433]
 [-0.29350827]
 [-0.78417223]
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 [ 1.43485164]
 [ 0.40601342]
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[[ 0.05505875 -0.15217168  0.04962112 ..., -0.14259426  0.17068633
  -0.19727478]
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  -0.23962079]
 [ 0.05826082 -0.03177198 -0.07961349 ...,  0.03791676  0.32180106
   0.19458869]]
Progress: 10.3% ... Training loss: 0.273 ... Validation loss: 0.446[[ 0.34373929]
 [-0.29827192]
 [-0.78825189]
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 [ 1.43174851]
 [ 0.4012267 ]
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[[ 0.05547115 -0.15252346  0.04882056 ..., -0.14269307  0.17183098
  -0.19785937]
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  -0.23947774]
 [ 0.05766798 -0.03124168 -0.07826841 ...,  0.03808598  0.32048521
   0.1960389 ]]
Progress: 10.3% ... Training loss: 0.274 ... Validation loss: 0.446[[ 0.35527005]
 [-0.2886812 ]
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 [ 1.43895581]
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[[ 0.05668701 -0.15360571  0.04615496 ..., -0.14304673  0.1747032
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 [-0.190854   -0.18870546 -0.12338582 ...,  0.10367655 -0.07086323
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  -0.23983133]
 [ 0.057725   -0.03130176 -0.07839478 ...,  0.03807168  0.32079994
   0.19586513]]
Progress: 10.3% ... Training loss: 0.282 ... Validation loss: 0.457[[ 0.34279915]
 [-0.2991373 ]
 [-0.79160681]
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[[ 0.05559458 -0.15269896  0.04856431 ..., -0.14275892  0.17204421
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  -0.23857432]
 [ 0.05732005 -0.03095242 -0.07753123 ...,  0.03817927  0.31992183
   0.19678102]]
Progress: 10.3% ... Training loss: 0.277 ... Validation loss: 0.449[[ 0.35239405]
 [-0.29202937]
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 [ 1.43656569]
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[[ 0.05650819 -0.15349869  0.04656305 ..., -0.14303952  0.17430273
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  -0.23940837]
 [ 0.05732129 -0.03092918 -0.07747394 ...,  0.03817344  0.32013372
   0.19687353]]
Progress: 10.3% ... Training loss: 0.274 ... Validation loss: 0.450[[ 0.35050594]
 [-0.2933075 ]
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 [ 1.43513128]
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[[ 0.05644175 -0.15345239  0.04681536 ..., -0.14303382  0.17419238
  -0.19983384]
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 [-0.19117616 -0.18845914 -0.12278211 ...,  0.10373773 -0.0717313
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  -0.23967351]
 [ 0.0574019  -0.03097925 -0.07765857 ...,  0.03815687  0.3205241
   0.19668722]]
Progress: 10.3% ... Training loss: 0.272 ... Validation loss: 0.447[[ 0.34254835]
 [-0.29990742]
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[[ 0.05663798 -0.15363193  0.0465087  ..., -0.14308664  0.17463704
  -0.20033262]
 [ 0.04266982  0.04491322  0.10510451 ..., -0.24527193 -0.02842511
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 [-0.19130879 -0.18835759 -0.12250437 ...,  0.10377638 -0.07205645
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  -0.23915536]
 [ 0.05758117 -0.03112319 -0.07804319 ...,  0.03811435  0.32099112
   0.19625423]]
Progress: 10.3% ... Training loss: 0.279 ... Validation loss: 0.448[[ 0.3516208 ]
 [-0.2920381 ]
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[[ 0.05824809 -0.1550371   0.04283871 ..., -0.14357078  0.17870177
  -0.20422735]
 [ 0.04251046  0.04505406  0.10546992 ..., -0.2452307  -0.02867104
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   0.46903223]
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 [-0.19127689 -0.1883866  -0.12257006 ...,  0.10376578 -0.0719794
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  -0.23995699]
 [ 0.05764337 -0.03115017 -0.07820022 ...,  0.03810586  0.32123035
   0.19610549]]
Progress: 10.3% ... Training loss: 0.275 ... Validation loss: 0.449[[ 0.3483193 ]
 [-0.29449096]
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[[ 0.05785268 -0.15469633  0.04364286 ..., -0.14346778  0.17770171
  -0.20353055]
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   0.11217911]
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   0.46915684]
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 [-0.19165194 -0.18807917 -0.12175669 ...,  0.10386358 -0.07288002
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  -0.23961615]
 [ 0.05763557 -0.03114115 -0.07821391 ...,  0.03811025  0.32123665
   0.19607149]]
Progress: 10.3% ... Training loss: 0.272 ... Validation loss: 0.445[[ 0.34529593]
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[[ 0.05762453 -0.15450669  0.04422114 ..., -0.14340823  0.1771817
  -0.20287168]
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 [-0.19144108 -0.18825766 -0.12217908 ...,  0.10380203 -0.07247799
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 [-0.27993863 -0.2253311  -0.05130083 ..., -0.11904214 -0.0240374
  -0.23925152]
 [ 0.05759708 -0.03109895 -0.07821463 ...,  0.03812041  0.32122763
   0.19597723]]
Progress: 10.3% ... Training loss: 0.274 ... Validation loss: 0.448[[ 0.35338607]
 [-0.29099841]
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[[ 0.05878096 -0.15551782  0.04168237 ..., -0.1437384   0.17982051
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 ..., 
 [-0.19149632 -0.18822783 -0.12198006 ...,  0.10381972 -0.07275168
  -0.04092175]
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  -0.2399462 ]
 [ 0.05825217 -0.03166308 -0.07966861 ...,  0.03793324  0.32288742
   0.19435822]]
Progress: 10.4% ... Training loss: 0.277 ... Validation loss: 0.456[[ 0.34364168]
 [-0.29886728]
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[[ 0.05799091 -0.15485468  0.04351297 ..., -0.14352888  0.17809541
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  -0.2394871 ]
 [ 0.05823765 -0.0316405  -0.07965043 ...,  0.03793046  0.32292928
   0.19416105]]
Progress: 10.4% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.33099517]
 [-0.30949969]
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[[ 0.05709041 -0.15407577  0.04559775 ..., -0.14325744  0.17599854
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   0.19461973]]
Progress: 10.4% ... Training loss: 0.322 ... Validation loss: 0.480[[ 0.3572026 ]
 [-0.28588536]
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[[ 0.0594479  -0.15625916  0.04009296 ..., -0.14406694  0.18189245
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  -0.23937415]
 [ 0.05849737 -0.03187411 -0.0803507  ...,  0.03782915  0.32378366
   0.19358579]]
Progress: 10.4% ... Training loss: 0.292 ... Validation loss: 0.471[[ 0.3411781 ]
 [-0.30081333]
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[[ 0.05835224 -0.15535616  0.04261576 ..., -0.14379787  0.17925483
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  -0.23863438]
 [ 0.05842924 -0.03182524 -0.08018358 ...,  0.0378516   0.32386094
   0.19374163]]
Progress: 10.4% ... Training loss: 0.278 ... Validation loss: 0.444[[ 0.34114556]
 [-0.30014225]
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[[ 0.05893086 -0.15583796  0.04128372 ..., -0.14395565  0.1808241
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  -0.23846759]
 [ 0.05819582 -0.03160346 -0.07970691 ...,  0.03792058  0.32356949
   0.19419197]]
Progress: 10.4% ... Training loss: 0.275 ... Validation loss: 0.440[[ 0.35460038]
 [-0.28823397]
 [-0.779617  ]
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 [ 1.45107103]
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[[ 0.0601236  -0.15691455  0.03851472 ..., -0.14428301  0.18303663
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  -0.23938926]
 [ 0.05850691 -0.03188703 -0.08045171 ...,  0.03782999  0.32438196
   0.19345062]]
Progress: 10.4% ... Training loss: 0.287 ... Validation loss: 0.465[[ 0.3424063 ]
 [-0.29820886]
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[[ 0.05994547 -0.15674639  0.03898387 ..., -0.14422925  0.18255537
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  -0.23924371]
 [ 0.0580985  -0.03154673 -0.07959075 ...,  0.03793337  0.32350277
   0.19426493]]
Progress: 10.4% ... Training loss: 0.272 ... Validation loss: 0.439[[ 0.36028062]
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[[ 0.06179408 -0.15840193  0.03477458 ..., -0.14476328  0.18697985
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  -0.23974553]
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   0.19167649]]
Progress: 10.4% ... Training loss: 0.315 ... Validation loss: 0.494[[ 0.33815153]
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[[ 0.06102793 -0.15777516  0.03647352 ..., -0.1445817   0.18541844
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 [-0.19180559 -0.18808211 -0.1215581  ...,  0.10381247 -0.07352256
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  -0.23929722]
 [ 0.05808047 -0.03163093 -0.0796587  ...,  0.0378943   0.3238907
   0.19384661]]
Progress: 10.4% ... Training loss: 0.280 ... Validation loss: 0.439[[ 0.34408661]
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[[ 0.0612088  -0.15797039  0.03604261 ..., -0.14465546  0.18565499
  -0.2123341 ]
 [ 0.04229861  0.04522613  0.10583049 ..., -0.24517603 -0.02902497
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 [-0.19136302 -0.18848959 -0.12251662 ...,  0.10367697 -0.07263189
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  -0.23916315]
 [ 0.05830018 -0.03183071 -0.08018688 ...,  0.0378265   0.32455549
   0.19333663]]
Progress: 10.4% ... Training loss: 0.273 ... Validation loss: 0.439[[ 0.34449952]
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[[ 0.06078112 -0.1575684   0.03721717 ..., -0.14452512  0.18470236
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  -0.23942537]
 [ 0.0581583  -0.03170139 -0.07983248 ...,  0.03786812  0.32421922
   0.19371545]]
Progress: 10.4% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.35037791]
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[[ 0.062043   -0.15870269  0.0343613  ..., -0.14492014  0.18761844
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 [ 0.04216869  0.04534045  0.10611653 ..., -0.24513983 -0.02934701
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 [-0.19149808 -0.18837791 -0.12224942 ...,  0.10371068 -0.07302824
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 [ 0.05854616 -0.03205396 -0.08080597 ...,  0.03774803  0.32508361
   0.19264796]]
Progress: 10.4% ... Training loss: 0.274 ... Validation loss: 0.452[[ 0.34282587]
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[[ 0.06106965 -0.15792383  0.03657291 ..., -0.14465549  0.18511269
  -0.21197831]
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 ..., 
 [-0.19194837 -0.18800672 -0.12120314 ...,  0.10383417 -0.07411223
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  -0.2380768 ]
 [ 0.05861878 -0.03211298 -0.08096462 ...,  0.03772326  0.32525406
   0.19246692]]
Progress: 10.4% ... Training loss: 0.277 ... Validation loss: 0.443[[ 0.34546353]
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[[ 0.06109363 -0.15797188  0.03649807 ..., -0.14466006  0.18514451
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   0.47746848]
 ..., 
 [-0.19192807 -0.18802849 -0.12120979 ...,  0.1038261  -0.07400293
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  -0.23812812]
 [ 0.05928811 -0.03270108 -0.08255478 ...,  0.03751963  0.32697276
   0.19092999]]
Progress: 10.4% ... Training loss: 0.274 ... Validation loss: 0.445[[ 0.35116005]
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[[ 0.06160057 -0.15845225  0.03528978 ..., -0.14483037  0.18642997
  -0.21332885]
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 [-0.19182245 -0.18812173 -0.12143493 ...,  0.10379177 -0.07379552
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 [ 0.05939014 -0.03277907 -0.08279455 ...,  0.03749446  0.32731859
   0.19069743]]
Progress: 10.5% ... Training loss: 0.273 ... Validation loss: 0.452[[ 0.35840035]
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[[ 0.0623495  -0.15907821  0.03372004 ..., -0.14503315  0.18814242
  -0.2152555 ]
 [ 0.04178726  0.04569009  0.10695102 ..., -0.24502194 -0.03023284
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   0.19025958]]
Progress: 10.5% ... Training loss: 0.296 ... Validation loss: 0.484[[ 0.334287  ]
 [-0.30743481]
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 [ 0.39364804]
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[[ 0.06061178 -0.15760629  0.03747233 ..., -0.144579    0.18396744
  -0.2116118 ]
 [ 0.04177679  0.04569742  0.10697215 ..., -0.2450201  -0.03024775
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  -0.23774599]
 [ 0.05864477 -0.03211424 -0.081277   ...,  0.03770095  0.32586046
   0.19226585]]
Progress: 10.5% ... Training loss: 0.293 ... Validation loss: 0.451[[ 0.35258759]
 [-0.29198829]
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[[ 0.06189468 -0.1587937   0.03450466 ..., -0.14496833  0.18713904
  -0.21453158]
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  -0.23856326]
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   0.19205182]]
Progress: 10.5% ... Training loss: 0.283 ... Validation loss: 0.459[[ 0.34409845]
 [-0.29875843]
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[[ 0.06098769 -0.15801048  0.03648154 ..., -0.14473092  0.18504732
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  -0.23814115]
 [ 0.05876501 -0.03221378 -0.08161945 ...,  0.03765266  0.3262174
   0.19172515]]
Progress: 10.5% ... Training loss: 0.273 ... Validation loss: 0.438[[ 0.35203989]
 [-0.29170619]
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[[ 0.06138208 -0.15836485  0.03564265 ..., -0.14484969  0.18588164
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 [ 0.05882008 -0.03224664 -0.08173165 ...,  0.03764246  0.32645146
   0.19159367]]
Progress: 10.5% ... Training loss: 0.278 ... Validation loss: 0.453[[ 0.3510971 ]
 [-0.29362721]
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[[ 0.06132497 -0.15836084  0.03582226 ..., -0.14484563  0.18581416
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  -0.23717148]
 [ 0.05853073 -0.03198438 -0.08106149 ...,  0.03772455  0.32614913  0.1922    ]]
Progress: 10.5% ... Training loss: 0.275 ... Validation loss: 0.447[[ 0.34470508]
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[[ 0.06031858 -0.15751993  0.03806018 ..., -0.14458311  0.18342323
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  -0.23719175]
 [ 0.0584401  -0.03190274 -0.0808584  ...,  0.03775094  0.32611151
   0.19243898]]
Progress: 10.5% ... Training loss: 0.273 ... Validation loss: 0.440[[ 0.36282989]
 [-0.28363404]
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[[ 0.06163189 -0.15866551  0.03508139 ..., -0.14496126  0.18652207
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   0.19045909]]
Progress: 10.5% ... Training loss: 0.311 ... Validation loss: 0.502[[ 0.3378937 ]
 [-0.30553026]
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[[ 0.0594922  -0.15693165  0.03964624 ..., -0.14444513  0.18187142
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 ..., 
 [-0.19223912 -0.18788534 -0.1205068  ...,  0.10385264 -0.0749531  -0.039612  ]
 [-0.28142133 -0.22422455 -0.04845146 ..., -0.11873024 -0.02820566
  -0.23634435]
 [ 0.05850856 -0.03195512 -0.08110808 ...,  0.03769924  0.32675606
   0.19198823]]
Progress: 10.5% ... Training loss: 0.290 ... Validation loss: 0.446[[ 0.3460566 ]
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[[ 0.0599076  -0.15732032  0.03870461 ..., -0.14458114  0.1831197
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 [-0.19230214 -0.18782896 -0.1203915  ...,  0.10387004 -0.07508675
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  -0.23764937]
 [ 0.05848209 -0.03191316 -0.08098438 ...,  0.0377102   0.32677762
   0.19209114]]
Progress: 10.5% ... Training loss: 0.273 ... Validation loss: 0.442[[ 0.35809566]
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[[ 0.06069494 -0.15794986  0.03704546 ..., -0.14480701  0.1852918
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 [-0.19189653 -0.18817095 -0.12122794 ...,  0.10374732 -0.07411923
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  -0.23850977]
 [ 0.05830959 -0.03172911 -0.08057044 ...,  0.03777251  0.32659943
   0.19249867]]
Progress: 10.5% ... Training loss: 0.291 ... Validation loss: 0.477[[ 0.35208531]
 [-0.29353431]
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[[ 0.06030689 -0.15760219  0.03783566 ..., -0.14471737  0.18463301
  -0.21047388]
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 [-0.19184614 -0.18819338 -0.12135607 ...,  0.1037336  -0.07403994
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  -0.23698912]
 [ 0.05796376 -0.0314424  -0.07986963 ...,  0.03786034  0.3260755
   0.1932604 ]]
Progress: 10.5% ... Training loss: 0.274 ... Validation loss: 0.449[[ 0.35245305]
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[[ 0.06073465 -0.15795282  0.0369825  ..., -0.14481629  0.18545758
  -0.21121371]
 [ 0.04118024  0.04618838  0.10822639 ..., -0.24487042 -0.03162208
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   0.48054886]
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 [-0.1911217  -0.18880563 -0.12291143 ...,  0.1035415  -0.07250633
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  -0.23725868]
 [ 0.05805079 -0.03150655 -0.08008388 ...,  0.0378402   0.32638728
   0.19305691]]
Progress: 10.5% ... Training loss: 0.275 ... Validation loss: 0.454[[ 0.35303954]
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[[ 0.06114744 -0.15831447  0.03613178 ..., -0.14492925  0.1865139
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 [ 0.04093471  0.04639543  0.10876989 ..., -0.24480955 -0.03222988
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 [-0.19121882 -0.18872589 -0.12267426 ...,  0.10356491 -0.07274111
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 [ 0.05875744 -0.03211053 -0.08162761 ...,  0.0376622   0.328056
   0.19126819]]
Progress: 10.5% ... Training loss: 0.275 ... Validation loss: 0.450[[ 0.34974301]
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[[ 0.06073096 -0.15798006  0.03703511 ..., -0.14482798  0.18553606
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 [ 0.04070912  0.0465923   0.10924085 ..., -0.24474667 -0.03279241
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 [-0.19145294 -0.18854153 -0.12217529 ...,  0.10362255 -0.07335604
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  -0.23781946]
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   0.19192056]]
Progress: 10.6% ... Training loss: 0.272 ... Validation loss: 0.442[[ 0.34387893]
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[[ 0.05908577 -0.15659137  0.04085563 ..., -0.14438583  0.18181116
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 [ 0.058197   -0.03161208 -0.08038697 ...,  0.03781689  0.3273811
   0.19249108]]
Progress: 10.6% ... Training loss: 0.279 ... Validation loss: 0.441[[ 0.35372772]
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[[ 0.05944112 -0.15684437  0.04011001 ..., -0.14446801  0.18257556
  -0.20807141]
 [ 0.04109384  0.04626174  0.10836424 ..., -0.24485578 -0.0318321   0.115278  ]
 [-0.0826769   0.04136396  0.098045   ...,  0.16845843 -0.12142543
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  -0.23871019]
 [ 0.05805358 -0.03147277 -0.08006983 ...,  0.0378676   0.32709561
   0.19293449]]
Progress: 10.6% ... Training loss: 0.276 ... Validation loss: 0.454[[ 0.34708105]
 [-0.29450366]
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 [ 1.45741241]
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[[ 0.05826102 -0.15583925  0.04271952 ..., -0.14413671  0.17975171
  -0.20543179]
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  -0.23843455]
 [ 0.05799311 -0.03140935 -0.07990092 ...,  0.03788435  0.32710766
   0.19309241]]
Progress: 10.6% ... Training loss: 0.271 ... Validation loss: 0.440[[ 0.3472248 ]
 [-0.29553648]
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 [ 1.45631013]
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[[ 0.05807593 -0.15569663  0.04318479 ..., -0.14411584  0.17969639
  -0.2049436 ]
 [ 0.04101019  0.0463333   0.1084857  ..., -0.24483337 -0.032001
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  -0.23870414]
 [ 0.05786123 -0.03130608 -0.07959209 ...,  0.0379177   0.32694869
   0.19343701]]
Progress: 10.6% ... Training loss: 0.272 ... Validation loss: 0.441[[ 0.34667542]
 [-0.29667259]
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 [-0.80139284]
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 [ 1.45741012]
 [ 0.40584558]
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[[ 0.0585635  -0.15609549  0.04220148 ..., -0.1442411   0.18088638
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  -0.23881605]
 [ 0.05793367 -0.03134261 -0.07982464 ...,  0.03789401  0.3271895
   0.19313414]]
Progress: 10.6% ... Training loss: 0.272 ... Validation loss: 0.440[[ 0.35140109]
 [-0.2914271 ]
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[[ 0.05816366 -0.15571152  0.04310607 ..., -0.14411962  0.17992539
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  -0.23912806]
 [ 0.05816383 -0.03154501 -0.0803447  ...,  0.03781992  0.32781194
   0.19260474]]
Progress: 10.6% ... Training loss: 0.273 ... Validation loss: 0.447[[ 0.34823358]
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[[ 0.05752027 -0.15516922  0.04450465 ..., -0.14395636  0.17862296
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  -0.23866201]
 [ 0.05838477 -0.03170106 -0.08081934 ...,  0.03776534  0.328395
   0.19199599]]
Progress: 10.6% ... Training loss: 0.270 ... Validation loss: 0.441[[ 0.34418953]
 [-0.29600493]
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[[ 0.05808673 -0.15560918  0.04327912 ..., -0.14410012  0.17960366
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 [ 0.05851988 -0.03178708 -0.08113771 ...,  0.03773107  0.3287502
   0.19168152]]
Progress: 10.6% ... Training loss: 0.272 ... Validation loss: 0.437[[ 0.35784378]
 [-0.28433372]
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[[ 0.05911476 -0.15649127  0.04102519 ..., -0.14442171  0.18221928
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 [ 0.05909196 -0.03226496 -0.08238604 ...,  0.03756654  0.3302019
   0.19043847]]
Progress: 10.6% ... Training loss: 0.293 ... Validation loss: 0.460[[ 0.35097588]
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[[ 0.05873713 -0.15615027  0.0419595  ..., -0.1443261   0.18156385
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 [-0.19185065 -0.18818427 -0.12129824 ...,  0.10375211 -0.074581
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 [ 0.05834376 -0.03161222 -0.08070565 ...,  0.03777138  0.32873879
   0.19206443]]
Progress: 10.6% ... Training loss: 0.275 ... Validation loss: 0.438[[ 0.33283621]
 [-0.30780054]
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[[ 0.05706269 -0.15477215  0.04557257 ..., -0.14387663  0.17747531
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 [-0.19250176 -0.18765225 -0.11987508 ...,  0.10392828 -0.07606769
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 [ 0.05798378 -0.03127212 -0.07994072 ...,  0.03788486  0.32803066
   0.19288494]]
Progress: 10.6% ... Training loss: 0.311 ... Validation loss: 0.473[[ 0.355629  ]
 [-0.28679195]
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[[ 0.05853046 -0.1561441   0.04223572 ..., -0.14435757  0.18110782
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  -0.23965348]
 [ 0.05835645 -0.03159281 -0.08082449 ...,  0.03777115  0.32908602
   0.19207063]]
Progress: 10.6% ... Training loss: 0.281 ... Validation loss: 0.456[[ 0.34642788]
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[[ 0.05702493 -0.15491942  0.04563538 ..., -0.14396444  0.17759995
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 [-0.19240352 -0.18779731 -0.1200865  ...,  0.10386264 -0.07578982
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  -0.23948132]
 [ 0.05794851 -0.0312512  -0.07992989 ...,  0.03788052  0.32834638
   0.19288472]]
Progress: 10.6% ... Training loss: 0.272 ... Validation loss: 0.440[[ 0.35354582]
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[[ 0.05711598 -0.15499271  0.04541202 ..., -0.14400076  0.17787546
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 ..., 
 [-0.19252397 -0.18768973 -0.11977792 ...,  0.10389053 -0.07618439
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  -0.23966489]
 [ 0.0584215  -0.03167659 -0.08101323 ...,  0.03773347  0.32966234
   0.19173248]]
Progress: 10.6% ... Training loss: 0.273 ... Validation loss: 0.447[[ 0.34853314]
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[[ 0.05676487 -0.1546834   0.04621305 ..., -0.1439041   0.17705565
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   0.1918819 ]]
Progress: 10.7% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.36063065]
 [-0.28340168]
 [-0.78131612]
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 [ 1.474782  ]
 [ 0.41690781]
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[[ 0.05779936 -0.15551903  0.04408128 ..., -0.14419553  0.17960825
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   0.19137095]]
Progress: 10.7% ... Training loss: 0.294 ... Validation loss: 0.470[[ 0.33503476]
 [-0.30513295]
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 [ 1.45518156]
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[[ 0.05510858 -0.1533687   0.04990898 ..., -0.14350349  0.17364774
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  -0.23809619]
 [ 0.05713417 -0.03063487 -0.07817376 ...,  0.03805135  0.32737858
   0.19475816]]
Progress: 10.7% ... Training loss: 0.308 ... Validation loss: 0.465[[ 0.36352219]
 [-0.28071423]
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 [ 1.47527531]
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[[ 0.05730477 -0.15543964  0.04462163 ..., -0.14425341  0.17896089
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  -0.23933912]
 [ 0.05820923 -0.03164017 -0.08073346 ...,  0.03768039  0.33000878
   0.19220402]]
Progress: 10.7% ... Training loss: 0.304 ... Validation loss: 0.480[[ 0.35271595]
 [-0.29095406]
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[[ 0.05749398 -0.15559152  0.0443936  ..., -0.14430657  0.17971205
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  -0.23951903]
 [ 0.0576882  -0.03118477 -0.07956269 ...,  0.0378208   0.32923574
   0.19354866]]
Progress: 10.7% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.35883076]
 [-0.28563747]
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 [ 1.47935339]
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[[ 0.05819055 -0.15618379  0.04301078 ..., -0.14450025  0.18137941
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  -0.24043123]
 [ 0.05801005 -0.03145237 -0.08020997 ...,  0.0377328   0.32997843
   0.19274454]]
Progress: 10.7% ... Training loss: 0.289 ... Validation loss: 0.461[[ 0.35101459]
 [-0.29439194]
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 [ 1.47263197]
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[[ 0.0575703  -0.15568811  0.04445476 ..., -0.14434729  0.1800716
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  -0.23984648]
 [ 0.05724421 -0.03080942 -0.07851184 ...,  0.03793887  0.32854275
   0.194491  ]]
Progress: 10.7% ... Training loss: 0.272 ... Validation loss: 0.439[[ 0.351467  ]
 [-0.29347261]
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[[ 0.05793243 -0.15597106  0.04369517 ..., -0.14444542  0.18071476
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 [ 0.05739288 -0.03093057 -0.07886122 ...,  0.03789734  0.32890982
   0.1941077 ]]
Progress: 10.7% ... Training loss: 0.273 ... Validation loss: 0.440[[ 0.35101691]
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[[ 0.05727782 -0.15542536  0.04523869 ..., -0.14426298  0.17904681
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 [ 0.05760467 -0.03110437 -0.07932047 ...,  0.03784115  0.32955778
   0.19358111]]
Progress: 10.7% ... Training loss: 0.272 ... Validation loss: 0.441[[ 0.35225472]
 [-0.29214912]
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[[ 0.05766925 -0.1557741   0.04445273 ..., -0.14439241  0.1800398
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  -0.24147267]
 [ 0.05788963 -0.03133991 -0.07999049 ...,  0.03776373  0.33027997
   0.19280051]]
Progress: 10.7% ... Training loss: 0.272 ... Validation loss: 0.446[[ 0.34664127]
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[[ 0.05683315 -0.1549984   0.04648479 ..., -0.14414177  0.17823436
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  -0.24148387]
 [ 0.05746011 -0.03097618 -0.07905727 ...,  0.0378749   0.32938231
   0.19366226]]
Progress: 10.7% ... Training loss: 0.271 ... Validation loss: 0.436[[ 0.35071695]
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[[ 0.05747611 -0.15553596  0.04504313 ..., -0.14432666  0.17968976
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 [ 0.05792589 -0.03137849 -0.08013815 ...,  0.03773678  0.33049576
   0.19257192]]
Progress: 10.7% ... Training loss: 0.272 ... Validation loss: 0.441[[ 0.33999547]
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[[ 0.05685603 -0.15496952  0.04660228 ..., -0.14414252  0.17836874
  -0.2042288 ]
 [ 0.04114907  0.0461778   0.10790828 ..., -0.24489101 -0.03114887
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 ..., 
 [-0.19183106 -0.18837224 -0.12130273 ...,  0.10360663 -0.0746197
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  -0.24182681]
 [ 0.05736063 -0.03085479 -0.07889614 ...,  0.03790311  0.32959243
   0.19394517]]
Progress: 10.7% ... Training loss: 0.278 ... Validation loss: 0.439[[ 0.33909195]
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[[ 0.05686078 -0.154984    0.04665143 ..., -0.14414591  0.17844013
  -0.20417413]
 [ 0.04123238  0.04610227  0.10771289 ..., -0.24491642 -0.03094812
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 [-0.19183388 -0.18836578 -0.12129805 ...,  0.10360856 -0.0746216
  -0.0409498 ]
 [-0.27912238 -0.22640684 -0.05406814 ..., -0.11952197 -0.0229091
  -0.24182772]
 [ 0.05728842 -0.03079223 -0.07871351 ...,  0.03792775  0.32948564
   0.1941258 ]]
Progress: 10.7% ... Training loss: 0.280 ... Validation loss: 0.441[[ 0.34422043]
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[[ 0.05713214 -0.15520786  0.04616359 ..., -0.14422472  0.17897571
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 [-0.19195673 -0.18825768 -0.12098611 ...,  0.10363597 -0.07488725
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 [ 0.05758804 -0.03106925 -0.07944622 ...,  0.0378334   0.3302812
   0.19341831]]
Progress: 10.7% ... Training loss: 0.273 ... Validation loss: 0.440[[ 0.34686509]
 [-0.29228964]
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[[ 0.05712769 -0.15518038  0.04624941 ..., -0.14422518  0.17873849
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   0.19248618]]
Progress: 10.8% ... Training loss: 0.271 ... Validation loss: 0.443[[ 0.34125201]
 [-0.29577311]
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 [ 1.46503906]
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[[ 0.05704288 -0.15510619  0.04646634 ..., -0.14420294  0.1784741
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   0.19340816]]
Progress: 10.8% ... Training loss: 0.274 ... Validation loss: 0.442[[ 0.35578387]
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 [ 1.47586269]
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[[ 0.05888259 -0.15669858  0.04238569 ..., -0.14476629  0.18278316
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  -0.24228675]
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   0.19383032]]
Progress: 10.8% ... Training loss: 0.292 ... Validation loss: 0.472[[ 0.33652664]
 [-0.29989031]
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[[ 0.05797855 -0.15595487  0.04441936 ..., -0.14452652  0.18074595
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   0.19487586]]
Progress: 10.8% ... Training loss: 0.282 ... Validation loss: 0.445[[ 0.34250785]
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[[ 0.0581744  -0.15606615  0.04418473 ..., -0.14457933  0.18158311
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   0.19454923]]
Progress: 10.8% ... Training loss: 0.272 ... Validation loss: 0.440[[ 0.34833044]
 [-0.28889371]
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[[ 0.05810457 -0.15602786  0.04435849 ..., -0.14454756  0.18136709
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   0.19497562]]
Progress: 10.8% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.33665348]
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[[ 0.05730472 -0.15535166  0.04616855 ..., -0.14432341  0.17943813
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 [ 0.05617364 -0.02979835 -0.07623722 ...,  0.03824295  0.32808343  0.19677   ]]
Progress: 10.8% ... Training loss: 0.282 ... Validation loss: 0.446[[ 0.34369966]
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[[ 0.05799955 -0.15597595  0.04462089 ..., -0.14453648  0.18087168
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   0.19615148]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.439[[ 0.34411927]
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[[ 0.05828585 -0.15622499  0.04393767 ..., -0.14463291  0.18141948
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   0.19700768]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.439[[ 0.34432942]
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[[ 0.05780379 -0.15578945  0.04504661 ..., -0.14448885  0.18038476
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 [ 0.05611056 -0.02970897 -0.07601183 ...,  0.03826795  0.32860773
   0.19690608]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.438[[ 0.34592116]
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[[ 0.05748869 -0.15546138  0.04592367 ..., -0.14437033  0.17986652
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 [ 0.05570189 -0.02930733 -0.07500647 ...,  0.03840671  0.32815938
   0.19792295]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.34381282]
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[[ 0.05688687 -0.1549315   0.04740733 ..., -0.14419427  0.17846673
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   0.19741284]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.34851807]
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[[ 0.05780896 -0.15575944  0.04532375 ..., -0.14446584  0.18056733
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  -0.24340097]
 [ 0.05592434 -0.0294846  -0.07547419 ...,  0.03835142  0.32880183
   0.1974942 ]]
Progress: 10.8% ... Training loss: 0.272 ... Validation loss: 0.444[[ 0.34392191]
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[[ 0.05659988 -0.15472004  0.04812181 ..., -0.14411332  0.1776628
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 [-0.19038967 -0.18961676 -0.12439984 ...,  0.10312442 -0.07135847
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 [ 0.05605171 -0.02958829 -0.07572624 ...,  0.03831673  0.32916551
   0.19717688]]
Progress: 10.8% ... Training loss: 0.270 ... Validation loss: 0.438[[ 0.33063118]
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[[ 0.05500191 -0.15331476  0.0519305  ..., -0.14364121  0.1737344
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 [ 0.05558044 -0.02916279 -0.07462349 ...,  0.03846264  0.32818684
   0.19810118]]
Progress: 10.8% ... Training loss: 0.302 ... Validation loss: 0.468[[ 0.35452636]
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[[ 0.05640721 -0.154572    0.04866339 ..., -0.14411962  0.17717695
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   0.19646521]]
Progress: 10.9% ... Training loss: 0.291 ... Validation loss: 0.469[[ 0.33115914]
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[[ 0.05484021 -0.15331161  0.05216453 ..., -0.14372009  0.17369317
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   0.19789553]]
Progress: 10.9% ... Training loss: 0.299 ... Validation loss: 0.467[[ 0.34943519]
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[[ 0.05623143 -0.15456072  0.04879784 ..., -0.14419271  0.17716341
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  -0.24483023]
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   0.19794713]]
Progress: 10.9% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.3464427 ]
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[[ 0.05553263 -0.15396928  0.05050841 ..., -0.14401701  0.17558739
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   0.19777351]]
Progress: 10.9% ... Training loss: 0.271 ... Validation loss: 0.443[[ 0.35052584]
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[[ 0.05648555 -0.1547676   0.04836476 ..., -0.14428634  0.17778512
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 [ 0.05609042 -0.0296152  -0.07582511 ...,  0.03829132  0.33000639
   0.19690071]]
Progress: 10.9% ... Training loss: 0.277 ... Validation loss: 0.445[[ 0.34043713]
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[[ 0.05476874 -0.15339996  0.05222325 ..., -0.14382817  0.17395976
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   0.19768654]]
Progress: 10.9% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.34908288]
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[[ 0.0555338  -0.15408834  0.05050144 ..., -0.14406497  0.17571757
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  -0.24330924]
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   0.19704911]]
Progress: 10.9% ... Training loss: 0.271 ... Validation loss: 0.440[[ 0.34794743]
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[[ 0.05516962 -0.15379439  0.05131371 ..., -0.14397944  0.17522206
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 [ 0.05584903 -0.02941876 -0.0752774  ...,  0.03836084  0.32999588
   0.19748052]]
Progress: 10.9% ... Training loss: 0.270 ... Validation loss: 0.444[[ 0.34597577]
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[[ 0.05418879 -0.1529364   0.05364958 ..., -0.14369723  0.1728016
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   0.19736954]]
Progress: 10.9% ... Training loss: 0.272 ... Validation loss: 0.445[[ 0.3508352 ]
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[[ 0.05470918 -0.15333049  0.05258465 ..., -0.14385348  0.17421186
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  -0.24316686]
 [ 0.05607504 -0.02959478 -0.0757609  ...,  0.03830115  0.33078373
   0.19693959]]
Progress: 10.9% ... Training loss: 0.271 ... Validation loss: 0.446[[ 0.34348614]
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[[ 0.05413802 -0.15285207  0.05385817 ..., -0.14368062  0.17280644
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  -0.24224561]
 [ 0.05610124 -0.02961878 -0.07584161 ...,  0.03830307  0.33092452
   0.19696998]]
Progress: 10.9% ... Training loss: 0.276 ... Validation loss: 0.448[[ 0.34932026]
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[[ 0.05411689 -0.15282034  0.05374878 ..., -0.14364975  0.1728492
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  -0.24248759]
 [ 0.05610931 -0.02960064 -0.0759411  ...,  0.03830481  0.33107518
   0.19689146]]
Progress: 10.9% ... Training loss: 0.270 ... Validation loss: 0.443[[ 0.3456125 ]
 [-0.28901223]
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[[ 0.05431351 -0.15295306  0.05343979 ..., -0.14368326  0.17295478
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  -0.24297849]
 [ 0.05600962 -0.02951958 -0.07572965 ...,  0.03833471  0.330887
   0.19713923]]
Progress: 10.9% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.34562319]
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[[ 0.05431126 -0.15285191  0.05352826 ..., -0.14364562  0.17285703
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 [-0.19042924 -0.18969327 -0.12467368 ...,  0.1030345  -0.07210926
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 [ 0.05537157 -0.02894665 -0.07429161 ...,  0.03854001  0.32952146
   0.19870841]]
Progress: 10.9% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.34792852]
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[[ 0.05460636 -0.15307787  0.05288007 ..., -0.14373281  0.17366775
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 [ 0.04079243  0.04644627  0.10829539 ..., -0.24483114 -0.03112151
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   0.19783964]]
Progress: 10.9% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.34327216]
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[[ 0.05367024 -0.15231048  0.05509195 ..., -0.14345453  0.171552
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  -0.24413219]
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   0.19807247]]
Progress: 11.0% ... Training loss: 0.273 ... Validation loss: 0.445[[ 0.3480492 ]
 [-0.28642363]
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 [ 1.47027754]
 [ 0.40648164]
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[[ 0.05333681 -0.15202659  0.05586716 ..., -0.1433422   0.17073234
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  -0.24390755]
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   0.19787256]]
Progress: 11.0% ... Training loss: 0.270 ... Validation loss: 0.444[[ 0.34870638]
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[[ 0.05289715 -0.15167135  0.05685667 ..., -0.14321574  0.16977185
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  -0.24392376]
 [ 0.05566945 -0.02917233 -0.07509034 ...,  0.03846892  0.33091028
   0.19830465]]
Progress: 11.0% ... Training loss: 0.270 ... Validation loss: 0.443[[ 0.33897445]
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[[ 0.05201372 -0.15092444  0.05882067 ..., -0.1429669   0.16787442
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  -0.24388917]
 [ 0.05500148 -0.02860375 -0.07364599 ...,  0.03866469  0.32965486
   0.1999247 ]]
Progress: 11.0% ... Training loss: 0.284 ... Validation loss: 0.460[[ 0.34147966]
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[[ 0.05211137 -0.15097543  0.05875915 ..., -0.14299221  0.16829198
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  -0.24339202]
 [ 0.0549438  -0.02853573 -0.0735121  ...,  0.03869164  0.32963607
   0.2000268 ]]
Progress: 11.0% ... Training loss: 0.276 ... Validation loss: 0.452[[ 0.35372983]
 [-0.27997688]
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[[ 0.0528563  -0.15156483  0.05709424 ..., -0.14320073  0.17013947
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 [ 0.0407085   0.04651016  0.10846128 ..., -0.24481884 -0.03111631
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 [ 0.05563192 -0.02912898 -0.07510318 ...,  0.03847527  0.33140538
   0.19846616]]
Progress: 11.0% ... Training loss: 0.278 ... Validation loss: 0.448[[ 0.33903133]
 [-0.29356246]
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[[ 0.05241761 -0.15116146  0.05819079 ..., -0.1430919   0.16931314
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 [ 0.0552445  -0.02879212 -0.07418165 ...,  0.03858428  0.33075996
   0.19937986]]
Progress: 11.0% ... Training loss: 0.279 ... Validation loss: 0.456[[ 0.35064631]
 [-0.28343435]
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[[ 0.05354768 -0.15213651  0.05565105 ..., -0.14343511  0.17195885
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  -0.24322694]
 [ 0.05598759 -0.02942925 -0.07596254 ...,  0.03835717  0.3327332
   0.19757551]]
Progress: 11.0% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.35294903]
 [-0.28344709]
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[[ 0.05399903 -0.15254116  0.05469744 ..., -0.14355927  0.1731637
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  -0.24327714]
 [ 0.05639587 -0.02978896 -0.07680832 ...,  0.03823677  0.33375848
   0.19657751]]
Progress: 11.0% ... Training loss: 0.274 ... Validation loss: 0.445[[ 0.36055967]
 [-0.27766156]
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[[ 0.05541942 -0.15373233  0.05156035 ..., -0.14395844  0.176468
  -0.19987531]
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 [-0.19127787 -0.18905031 -0.1228368  ...,  0.10322853 -0.07449343
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  -0.24359673]
 [ 0.05659206 -0.0299342  -0.07727532 ...,  0.03818042  0.33447207
   0.19594276]]
Progress: 11.0% ... Training loss: 0.298 ... Validation loss: 0.468[[ 0.33773497]
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[[ 0.05346976 -0.15220609  0.05574997 ..., -0.14345331  0.17173454
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 [-0.1918243  -0.18864105 -0.12166044 ...,  0.10336656 -0.07592321
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  -0.24241035]
 [ 0.05567822 -0.0291892  -0.07539003 ...,  0.03842969  0.33250469
   0.19802049]]
Progress: 11.0% ... Training loss: 0.293 ... Validation loss: 0.468[[ 0.35021465]
 [-0.28596261]
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[[ 0.05481585 -0.15342546  0.05267869 ..., -0.14390447  0.1750182
  -0.19884959]
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 [-0.19170076 -0.18875701 -0.12194815 ...,  0.10332128 -0.07560033
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  -0.24435962]
 [ 0.05540474 -0.02888491 -0.07474873 ...,  0.03854518  0.33203273
   0.19887077]]
Progress: 11.0% ... Training loss: 0.272 ... Validation loss: 0.447[[ 0.35063585]
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[[ 0.05468073 -0.15332857  0.05291355 ..., -0.1438883   0.17469023
  -0.19884411]
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   0.11528395]
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 [-0.19189377 -0.18860343 -0.12147793 ...,  0.1033759  -0.07607343
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  -0.24435921]
 [ 0.05539086 -0.02884388 -0.07468895 ...,  0.03856037  0.33205685
   0.19888295]]
Progress: 11.0% ... Training loss: 0.272 ... Validation loss: 0.446[[ 0.34750116]
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[[ 0.05528089 -0.15385544  0.05155577 ..., -0.14408085  0.17623814
  -0.19992334]
 [ 0.04081437  0.04639377  0.10813774 ..., -0.24488288 -0.03044663
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 [-0.19149724 -0.18892663 -0.1222988  ...,  0.1032607  -0.07510818
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  -0.24435356]
 [ 0.05537732 -0.02879138 -0.07470582 ...,  0.03857885  0.33231901
   0.1989983 ]]
Progress: 11.0% ... Training loss: 0.270 ... Validation loss: 0.445[[ 0.34797386]
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[[ 0.05525518 -0.15382929  0.05166293 ..., -0.14407611  0.17626668
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   0.19907732]]
Progress: 11.0% ... Training loss: 0.270 ... Validation loss: 0.443[[ 0.35295827]
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[[ 0.05529277 -0.1538455   0.05151235 ..., -0.14408237  0.17636525
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   0.19854958]]
Progress: 11.1% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.3444386 ]
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   0.19891655]]
Progress: 11.1% ... Training loss: 0.271 ... Validation loss: 0.444[[ 0.35479081]
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[[ 0.05557203 -0.15410197  0.05087631 ..., -0.14419996  0.1766537
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  -0.24520735]
 [ 0.05655981 -0.02979799 -0.07743815 ...,  0.03822314  0.33584357
   0.19607515]]
Progress: 11.1% ... Training loss: 0.278 ... Validation loss: 0.452[[ 0.34564455]
 [-0.29161205]
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   0.19706303]]
Progress: 11.1% ... Training loss: 0.271 ... Validation loss: 0.443[[ 0.33599408]
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   0.19880088]]
Progress: 11.1% ... Training loss: 0.292 ... Validation loss: 0.461[[ 0.35054747]
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[[ 0.05370723 -0.15245676  0.05524438 ..., -0.1436372   0.17209722
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   0.19745876]]
Progress: 11.1% ... Training loss: 0.272 ... Validation loss: 0.447[[ 0.34118372]
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[[ 0.05315917 -0.15200617  0.05644393 ..., -0.14348559  0.17089467 -0.19504   ]
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   0.20017537]]
Progress: 11.1% ... Training loss: 0.276 ... Validation loss: 0.450[[ 0.3446221 ]
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[[ 0.05329647 -0.15212335  0.0561594  ..., -0.14350641  0.17121946
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 [ 0.05464953 -0.02813166 -0.0733525  ...,  0.03879878  0.33228458
   0.20051594]]
Progress: 11.1% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.34705688]
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[[ 0.05476953 -0.15336684  0.05304246 ..., -0.14393301  0.17486211
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 [ 0.05394356 -0.02752396 -0.07173642 ...,  0.03902457  0.33093662
   0.20226116]]
Progress: 11.1% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.34371008]
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[[ 0.05468625 -0.153311    0.05346081 ..., -0.14391536  0.17462105
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   0.20340583]]
Progress: 11.1% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.34781935]
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[[ 0.05471671 -0.15335241  0.05341694 ..., -0.14393637  0.17488069
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 [ 0.05383418 -0.02742191 -0.0713788  ...,  0.03906459  0.33099791
   0.20259639]]
Progress: 11.1% ... Training loss: 0.270 ... Validation loss: 0.443[[ 0.34947046]
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[[ 0.05534502 -0.15386181  0.05209013 ..., -0.14411856  0.17643752
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 [ 0.0534217  -0.02704562 -0.07041138 ...,  0.03920191  0.33027643
   0.20360679]]
Progress: 11.1% ... Training loss: 0.274 ... Validation loss: 0.446[[ 0.34750543]
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[[ 0.05632413 -0.15467463  0.04999562 ..., -0.14439758  0.17851448
  -0.2014091 ]
 [ 0.04048593  0.04667366  0.10860188 ..., -0.24477914 -0.03112735
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 [ 0.05317047 -0.02683686 -0.06993545 ...,  0.03927292  0.32965695
   0.2040184 ]]
Progress: 11.1% ... Training loss: 0.272 ... Validation loss: 0.443[[ 0.34239986]
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[[ 0.05575487 -0.15418646  0.05125312 ..., -0.14424156  0.17721844
  -0.2001518 ]
 [ 0.04068571  0.04650979  0.10816221 ..., -0.24483375 -0.03062678
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   0.2039289 ]]
Progress: 11.1% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.34338096]
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   0.20305051]]
Progress: 11.1% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.33565462]
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[[ 0.053765   -0.15237807  0.05602777 ..., -0.1436224   0.17276439
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   0.20220518]]
Progress: 11.2% ... Training loss: 0.278 ... Validation loss: 0.450[[ 0.34097984]
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[[ 0.05410957 -0.15270401  0.05531073 ..., -0.1437391   0.17386494
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   0.20108069]]
Progress: 11.2% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.35358378]
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[[ 0.05557981 -0.15398604  0.051939   ..., -0.14418156  0.17749567
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   0.20042782]]
Progress: 11.2% ... Training loss: 0.287 ... Validation loss: 0.463[[ 0.33093894]
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[[ 0.05382302 -0.15256445  0.05584352 ..., -0.14370928  0.17331177
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   0.19978353]]
Progress: 11.2% ... Training loss: 0.295 ... Validation loss: 0.461[[ 0.35519907]
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 [ 0.05504273 -0.02839367 -0.07418435 ...,  0.03871643  0.33517471
   0.19962037]]
Progress: 11.2% ... Training loss: 0.296 ... Validation loss: 0.479[[ 0.34966615]
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[[ 0.0561607  -0.15466519  0.05037393 ..., -0.14446005  0.17918637
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   0.19926327]]
Progress: 11.2% ... Training loss: 0.281 ... Validation loss: 0.457[[ 0.33525232]
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 [ 0.0548833  -0.02825458 -0.07378046 ...,  0.03876947  0.33521034
   0.19992403]]
Progress: 11.2% ... Training loss: 0.280 ... Validation loss: 0.450[[ 0.3481358 ]
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[[ 0.05633522 -0.15490836  0.04996707 ..., -0.14459218  0.18013233
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 [ 0.05532381 -0.02863653 -0.07483447 ...,  0.03863565  0.33641859
   0.19877767]]
Progress: 11.2% ... Training loss: 0.276 ... Validation loss: 0.451[[ 0.33392075]
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[[ 0.05515306 -0.15393546  0.05265573 ..., -0.14425965  0.17715288
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 [ 0.0553983  -0.0286733  -0.07506832 ...,  0.03862212  0.33672489
   0.19853804]]
Progress: 11.2% ... Training loss: 0.280 ... Validation loss: 0.448[[ 0.34219309]
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[[ 0.05545366 -0.1542509   0.05198554 ..., -0.14436927  0.17781696
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 [ 0.0556043  -0.02885856 -0.07549076 ...,  0.0385553   0.33727407
   0.19788835]]
Progress: 11.2% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.34365961]
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[[ 0.05561605 -0.15436978  0.05164593 ..., -0.14440081  0.17824736
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 [ 0.05571751 -0.02894672 -0.07581111 ...,  0.038528    0.3376312
   0.19763083]]
Progress: 11.2% ... Training loss: 0.269 ... Validation loss: 0.442[[ 0.33709311]
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[[ 0.05547221 -0.15423128  0.05197112 ..., -0.14437458  0.17797769
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 ..., 
 [-0.19312082 -0.18771492 -0.11916877 ...,  0.10360842 -0.08005903
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  -0.24739227]
 [ 0.05539344 -0.02864943 -0.075124   ...,  0.03862754  0.33713101
   0.19843061]]
Progress: 11.2% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.34047072]
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[[ 0.05580872 -0.15449197  0.05131525 ..., -0.14446239  0.1788477
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 [ 0.05513408 -0.02841458 -0.07448991 ...,  0.03870806  0.33659364
   0.19906497]]
Progress: 11.2% ... Training loss: 0.269 ... Validation loss: 0.439[[ 0.34433393]
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[[ 0.05619207 -0.15476496  0.0505446  ..., -0.14456322  0.18005373
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 [-0.19277834 -0.18801868 -0.119868   ...,  0.10349935 -0.07919356
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   0.19795054]]
Progress: 11.2% ... Training loss: 0.274 ... Validation loss: 0.441[[ 0.33451609]
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[[ 0.05519699 -0.15393495  0.05271203 ..., -0.14428354  0.17789834
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   0.20000302]]
Progress: 11.2% ... Training loss: 0.275 ... Validation loss: 0.439[[ 0.34289518]
 [-0.28822227]
 [-0.77730496]
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 [ 0.40800454]
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[[ 0.05542512 -0.15412625  0.05223569 ..., -0.14435302  0.17832021
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  -0.24780062]
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   0.19989084]]
Progress: 11.3% ... Training loss: 0.272 ... Validation loss: 0.437[[ 0.33728649]
 [-0.29264323]
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 [ 1.49075349]
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[[ 0.05469244 -0.15351307  0.05397682 ..., -0.14415074  0.17645147
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  -0.24678191]
 [ 0.05469597 -0.02799537 -0.07358301 ...,  0.03883348  0.33634215
   0.20002609]]
Progress: 11.3% ... Training loss: 0.271 ... Validation loss: 0.438[[ 0.34420063]
 [-0.28635466]
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[[ 0.05438903 -0.15324244  0.0546969  ..., -0.14405629  0.17571603
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  -0.2458307 ]
 [ 0.05482024 -0.02808885 -0.07386599 ...,  0.03880218  0.33686552
   0.19978851]]
Progress: 11.3% ... Training loss: 0.271 ... Validation loss: 0.440[[ 0.34698028]
 [-0.28412406]
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[[ 0.05498914 -0.15373009  0.05339483 ..., -0.14421363  0.17744965
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  -0.24536695]
 [ 0.05470495 -0.02792391 -0.07363734 ...,  0.03885175  0.33701199
   0.20011709]]
Progress: 11.3% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.33239927]
 [-0.29805718]
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[[ 0.05310729 -0.15213138  0.05763851 ..., -0.14368737  0.1729457
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  -0.24534703]
 [ 0.05475312 -0.02795417 -0.07379722 ...,  0.03883698  0.33728161
   0.1998903 ]]
Progress: 11.3% ... Training loss: 0.287 ... Validation loss: 0.452[[ 0.34605667]
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[[ 0.05412954 -0.15301889  0.0553325  ..., -0.14399492  0.17555361
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 [ 0.05481891 -0.02798358 -0.07395187 ...,  0.03883328  0.33776008
   0.19976978]]
Progress: 11.3% ... Training loss: 0.271 ... Validation loss: 0.442[[ 0.33553234]
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[[ 0.05335568 -0.15235727  0.05710708 ..., -0.14377909  0.17387647
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   0.19966164]]
Progress: 11.3% ... Training loss: 0.281 ... Validation loss: 0.447[[ 0.34583893]
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[[ 0.05379396 -0.15273226  0.05618431 ..., -0.14393213  0.17525351
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  -0.24538003]
 [ 0.05534074 -0.02842638 -0.07511141 ...,  0.03866532  0.33948984
   0.19870647]]
Progress: 11.3% ... Training loss: 0.269 ... Validation loss: 0.443[[ 0.34981581]
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[[ 0.05383452 -0.15271246  0.05626382 ..., -0.143921    0.17500405
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 ..., 
 [-0.19171141 -0.18895731 -0.12226428 ...,  0.10317066 -0.07685641
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  -0.24495595]
 [ 0.05567367 -0.02870596 -0.0758636  ...,  0.03857819  0.3402846
   0.19781246]]
Progress: 11.3% ... Training loss: 0.274 ... Validation loss: 0.449[[ 0.3373864 ]
 [-0.29602109]
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[[ 0.05319954 -0.15220475  0.05768342 ..., -0.1437603   0.17355605
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 [-0.19186787 -0.18882803 -0.12190857 ...,  0.10320437 -0.07725386
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 [ 0.05499448 -0.02813666 -0.07438574 ...,  0.03876329  0.3388502
   0.19942272]]
Progress: 11.3% ... Training loss: 0.280 ... Validation loss: 0.444[[ 0.33914533]
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[[ 0.0534033  -0.15231669  0.05738488 ..., -0.14379925  0.17399289
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 [ 0.0408202   0.04645633  0.10769519 ..., -0.2448784  -0.02985349
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 [-0.19144815 -0.18919449 -0.12281259 ...,  0.10307247 -0.07642181
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  -0.24484258]
 [ 0.05467714 -0.02784183 -0.0737153  ...,  0.03887374  0.33830432
   0.20002068]]
Progress: 11.3% ... Training loss: 0.272 ... Validation loss: 0.440[[ 0.34613107]
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[[ 0.05388396 -0.15268115  0.05637902 ..., -0.1439322   0.17533143
  -0.19631084]
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 [-0.19144231 -0.18919555 -0.12283961 ...,  0.10306964 -0.07638057
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  -0.2454139 ]
 [ 0.05501823 -0.0281426  -0.07447369 ...,  0.03876997  0.33919411
   0.19918698]]
Progress: 11.3% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.33053934]
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[[ 0.05223557 -0.15133093  0.0601124  ..., -0.14348055  0.1712712
  -0.19254764]
 [ 0.04099423  0.04631169  0.10731137 ..., -0.24492781 -0.02939704
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 ..., 
 [-0.19171571 -0.18897034 -0.12223725 ...,  0.10314446 -0.0770421
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  -0.24429736]
 [ 0.05450944 -0.02771762 -0.0733221  ...,  0.03891003  0.33814792
   0.20035204]]
Progress: 11.3% ... Training loss: 0.301 ... Validation loss: 0.463[[ 0.35474708]
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[[ 0.05368058 -0.15266949  0.05677762 ..., -0.14395153  0.17486097
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 [-0.19166885 -0.18902484 -0.1223507  ...,  0.10312844 -0.0769353
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   0.19930309]]
Progress: 11.3% ... Training loss: 0.289 ... Validation loss: 0.473[[ 0.33751572]
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[[ 0.05203542 -0.15135536  0.06040969 ..., -0.14353423  0.17107683
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   0.19952126]]
Progress: 11.3% ... Training loss: 0.277 ... Validation loss: 0.446[[ 0.3433507 ]
 [-0.28816665]
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   0.20013218]]
Progress: 11.4% ... Training loss: 0.270 ... Validation loss: 0.449[[ 0.34192911]
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[[ 0.05216721 -0.1514882   0.06025146 ..., -0.14356635  0.17125725
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  -0.24539446]
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   0.19933835]]
Progress: 11.4% ... Training loss: 0.271 ... Validation loss: 0.446[[ 0.3436227 ]
 [-0.28988108]
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[[ 0.0521889  -0.1514775   0.06025338 ..., -0.14357898  0.17131451
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   0.19821588]]
Progress: 11.4% ... Training loss: 0.269 ... Validation loss: 0.446[[ 0.338521  ]
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[[ 0.05278004 -0.15186202  0.05902202 ..., -0.14372988  0.17278891
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   0.19815277]]
Progress: 11.4% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.34058255]
 [-0.29098474]
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[[ 0.05327033 -0.15226888  0.05800105 ..., -0.14385178  0.1741111
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 [ 0.05504938 -0.02811424 -0.07463553 ...,  0.03878736  0.34035814
   0.19890231]]
Progress: 11.4% ... Training loss: 0.269 ... Validation loss: 0.442[[ 0.34234889]
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[[ 0.05303378 -0.15208515  0.05865123 ..., -0.14379473  0.17358148
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   0.19898297]]
Progress: 11.4% ... Training loss: 0.269 ... Validation loss: 0.445[[ 0.34632945]
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[[ 0.05323993 -0.15224402  0.05818711 ..., -0.14383894  0.17414017
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   0.19895192]]
Progress: 11.4% ... Training loss: 0.273 ... Validation loss: 0.451[[ 0.33733663]
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[[ 0.05304328 -0.15207096  0.05865916 ..., -0.14378487  0.1736141
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 [ 0.05483248 -0.02788759 -0.07412275 ...,  0.03885765  0.3402991
   0.19936868]]
Progress: 11.4% ... Training loss: 0.272 ... Validation loss: 0.441[[ 0.34621405]
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[[ 0.05417526 -0.15303571  0.05610357 ..., -0.14412079  0.17664825
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 [ 0.05495176 -0.02798555 -0.07437401 ...,  0.03882446  0.34070626
   0.19911483]]
Progress: 11.4% ... Training loss: 0.272 ... Validation loss: 0.450[[ 0.33169423]
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[[ 0.05293875 -0.15198064  0.05881991 ..., -0.14379108  0.17375996
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 [ 0.05528531 -0.02825815 -0.07508006 ...,  0.03873995  0.34157925
   0.19835825]]
Progress: 11.4% ... Training loss: 0.287 ... Validation loss: 0.449[[ 0.34788807]
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[[ 0.0537416  -0.15271975  0.05697171 ..., -0.14404087  0.17586875
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 [-0.19026916 -0.19029386 -0.1254448  ...,  0.10267586 -0.07403017
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 [ 0.05536284 -0.02833059 -0.07535202 ...,  0.03871293  0.34195676
   0.19811792]]
Progress: 11.4% ... Training loss: 0.274 ... Validation loss: 0.451[[ 0.33618463]
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[[ 0.0532207  -0.15227099  0.05817977 ..., -0.14388827  0.1745005
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 [-0.19063173 -0.18999029 -0.1247449  ...,  0.10276934 -0.07499555
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  -0.24344815]
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   0.1984215 ]]
Progress: 11.4% ... Training loss: 0.275 ... Validation loss: 0.442[[ 0.3433569 ]
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[[ 0.053973   -0.15292931  0.05658301 ..., -0.1441107   0.17625611
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   0.19882021]]
Progress: 11.4% ... Training loss: 0.268 ... Validation loss: 0.442[[ 0.34628256]
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[[ 0.05424278 -0.15306884  0.05629222 ..., -0.14416593  0.17713166
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   0.19797222]]
Progress: 11.4% ... Training loss: 0.272 ... Validation loss: 0.446[[ 0.33057626]
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[[ 0.05334816 -0.1523043   0.05844579 ..., -0.14393882  0.17495778
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   0.19768228]]
Progress: 11.4% ... Training loss: 0.287 ... Validation loss: 0.450[[ 0.34224244]
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[[ 0.0546771  -0.15349271  0.05533892 ..., -0.14433925  0.17869502
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   0.19710106]]
Progress: 11.5% ... Training loss: 0.270 ... Validation loss: 0.440[[ 0.33919027]
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[[ 0.05435275 -0.15323811  0.05613351 ..., -0.14425805  0.17782429
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   0.19740154]]
Progress: 11.5% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.34216024]
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[[ 0.05471652 -0.1535642   0.05534315 ..., -0.14435779  0.17864369
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   0.19651667]]
Progress: 11.5% ... Training loss: 0.268 ... Validation loss: 0.441[[ 0.341773  ]
 [-0.28882906]
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[[ 0.05470278 -0.1535497   0.05539306 ..., -0.14436125  0.17878297
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   0.19624425]]
Progress: 11.5% ... Training loss: 0.269 ... Validation loss: 0.439[[ 0.33716184]
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[[ 0.05465218 -0.15352441  0.05559992 ..., -0.14435392  0.17861303
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   0.19732506]]
Progress: 11.5% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.34281661]
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[[ 0.05517928 -0.1539942   0.05445715 ..., -0.14452026  0.17983662
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 [ 0.05580092 -0.02858731 -0.07637289 ...,  0.03859989  0.34458671
   0.19614571]]
Progress: 11.5% ... Training loss: 0.268 ... Validation loss: 0.440[[ 0.33980092]
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[[ 0.05518075 -0.15399547  0.05449177 ..., -0.14452538  0.17983556
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   0.19619742]]
Progress: 11.5% ... Training loss: 0.267 ... Validation loss: 0.440[[ 0.33479736]
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[[ 0.05505444 -0.15382345  0.05487321 ..., -0.14447326  0.17956919
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   0.19633139]]
Progress: 11.5% ... Training loss: 0.271 ... Validation loss: 0.440[[ 0.32949794]
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[[ 0.05439632 -0.15322655  0.05657898 ..., -0.14426705  0.17848346
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   0.19798495]]
Progress: 11.5% ... Training loss: 0.285 ... Validation loss: 0.451[[ 0.34169103]
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[[ 0.05510231 -0.15385148  0.05508519 ..., -0.1444859   0.18028484
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  -0.24666839]
 [ 0.05492078 -0.02772641 -0.07441928 ...,  0.03890092  0.34317428
   0.19828681]]
Progress: 11.5% ... Training loss: 0.269 ... Validation loss: 0.444[[ 0.32240649]
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[[ 0.05335873 -0.15233807  0.0590969  ..., -0.14400472  0.17634023
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 [-0.19096761 -0.18977446 -0.1239109  ...,  0.10283639 -0.07615282
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  -0.24630951]
 [ 0.05507939 -0.02784887 -0.07476705 ...,  0.03885662  0.34382614
   0.19798089]]
Progress: 11.5% ... Training loss: 0.321 ... Validation loss: 0.480[[ 0.34252589]
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[[ 0.05464923 -0.15361733  0.05609596 ..., -0.14445263  0.17982813
  -0.19676916]
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 [-0.1905644  -0.19016066 -0.12482241 ...,  0.10269732 -0.07514523
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  -0.2472456 ]
 [ 0.05507291 -0.02784575 -0.07472733 ...,  0.03885871  0.34392097
   0.19810177]]
Progress: 11.5% ... Training loss: 0.270 ... Validation loss: 0.446[[ 0.34402401]
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[[ 0.05500276 -0.15389419  0.05540958 ..., -0.14455778  0.18053633
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 [ 0.05524788 -0.0279934  -0.0751016  ...,  0.03881071  0.34431598
   0.19761675]]
Progress: 11.5% ... Training loss: 0.272 ... Validation loss: 0.452[[ 0.33596346]
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   0.19880854]]
Progress: 11.5% ... Training loss: 0.271 ... Validation loss: 0.443[[ 0.34275868]
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[[ 0.05417113 -0.15317012  0.05721626 ..., -0.14431163  0.17852455
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   0.19854291]]
Progress: 11.5% ... Training loss: 0.270 ... Validation loss: 0.447[[ 0.33675895]
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[[ 0.05433009 -0.15331582  0.05697563 ..., -0.14436937  0.17905639
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  -0.24530497]
 [ 0.05472149 -0.02753603 -0.07406005 ...,  0.03894812  0.34338577
   0.19867977]]
Progress: 11.6% ... Training loss: 0.269 ... Validation loss: 0.441[[ 0.33921099]
 [-0.29151048]
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[[ 0.05428823 -0.15329467  0.05714265 ..., -0.144354    0.17915048
  -0.1961259 ]
 [ 0.04156509  0.0457742   0.10558185 ..., -0.24512173 -0.02769022
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  -0.24551933]
 [ 0.0542141  -0.0270639  -0.07287401 ...,  0.03910847  0.3423544
   0.19994028]]
Progress: 11.6% ... Training loss: 0.269 ... Validation loss: 0.442[[ 0.33257702]
 [-0.29729813]
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[[ 0.0539965  -0.15303551  0.05788047 ..., -0.14425798  0.1784022
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 [ 0.05419771 -0.027027   -0.07282045 ...,  0.03912369  0.34260841
   0.19983976]]
Progress: 11.6% ... Training loss: 0.276 ... Validation loss: 0.446[[ 0.3508446 ]
 [-0.27948015]
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 [ 1.50179526]
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[[ 0.05534038 -0.1542265   0.05471282 ..., -0.1446638   0.18196448
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  -0.24693396]
 [ 0.05439812 -0.02717508 -0.07328716 ...,  0.03906555  0.34318755
   0.19925502]]
Progress: 11.6% ... Training loss: 0.296 ... Validation loss: 0.478[[ 0.32629162]
 [-0.30025116]
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[[ 0.05405193 -0.15313238  0.05763262 ..., -0.14430568  0.17893441
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  -0.2470119 ]
 [ 0.05383206 -0.02664943 -0.07206125 ...,  0.03922945  0.34222316
   0.20056112]]
Progress: 11.6% ... Training loss: 0.292 ... Validation loss: 0.461[[ 0.34693949]
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[[ 0.05590755 -0.15483638  0.05336373 ..., -0.1449411   0.18363549
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 [ 0.05475206 -0.02749206 -0.07437383 ...,  0.03893156  0.34468815
   0.19799665]]
Progress: 11.6% ... Training loss: 0.288 ... Validation loss: 0.469[[ 0.33336607]
 [-0.29306129]
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[[ 0.0554817  -0.15444211  0.05426422 ..., -0.14481135  0.1831703
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 [-0.19100455 -0.18987979 -0.12408877 ...,  0.1027428  -0.07628806
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  -0.24786537]
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   0.19832793]]
Progress: 11.6% ... Training loss: 0.268 ... Validation loss: 0.439[[ 0.32825331]
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[[ 0.05501183 -0.15404045  0.05546919 ..., -0.14467781  0.18200721
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 [ 0.05432019 -0.02707196 -0.07340722 ...,  0.03906436  0.34414143
   0.19903754]]
Progress: 11.6% ... Training loss: 0.276 ... Validation loss: 0.446[[ 0.33710718]
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[[ 0.05591258 -0.15486242  0.05333139 ..., -0.14497598  0.18423576
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  -0.24815028]
 [ 0.05464067 -0.02736387 -0.07419849 ...,  0.03895576  0.34510107
   0.19800387]]
Progress: 11.6% ... Training loss: 0.269 ... Validation loss: 0.438[[ 0.33947965]
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[[ 0.0563812  -0.15530285  0.052282   ..., -0.14511711  0.18519522
  -0.20087331]
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 [-0.19087255 -0.18999303 -0.12435165 ...,  0.10269752 -0.07600117
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 [ 0.05500738 -0.02765626 -0.07502272 ...,  0.03885317  0.34599967
   0.19697925]]
Progress: 11.6% ... Training loss: 0.273 ... Validation loss: 0.443[[ 0.32704635]
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[[ 0.055344   -0.15442642  0.05457546 ..., -0.14482203  0.18283375
  -0.1986032 ]
 [ 0.04167723  0.04565202  0.10517144 ..., -0.24516668 -0.02714531
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 ..., 
 [-0.19086084 -0.1900005  -0.12438141 ...,  0.10269334 -0.07589855
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 [ 0.05432074 -0.02705332 -0.07353827 ...,  0.03905835  0.34464828
   0.19861738]]
Progress: 11.6% ... Training loss: 0.278 ... Validation loss: 0.449[[ 0.34474369]
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[[ 0.05672898 -0.15572119  0.05136593 ..., -0.14528449  0.18638419
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 [-0.19036069 -0.19045467 -0.12544476 ...,  0.10252972 -0.07470164
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  -0.24836491]
 [ 0.05495272 -0.02763577 -0.07511884 ...,  0.03885712  0.34639455
   0.19726807]]
Progress: 11.6% ... Training loss: 0.285 ... Validation loss: 0.454[[ 0.32629056]
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[[ 0.05537461 -0.15454444  0.05436699 ..., -0.14492397  0.18316491
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 [ 0.05434844 -0.02710666 -0.07391291 ...,  0.03902728  0.34528195
   0.19863547]]
Progress: 11.6% ... Training loss: 0.278 ... Validation loss: 0.448[[ 0.34140331]
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[[ 0.05668772 -0.15577499  0.05128726 ..., -0.14532958  0.18621914
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   0.19835471]]
Progress: 11.6% ... Training loss: 0.276 ... Validation loss: 0.443[[ 0.32425712]
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[[ 0.0555994  -0.15479003  0.05379885 ..., -0.14501576  0.18382085
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   0.19942292]]
Progress: 11.6% ... Training loss: 0.284 ... Validation loss: 0.452[[ 0.33867815]
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[[ 0.05619504 -0.15536392  0.05246876 ..., -0.1452138   0.18538409
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  -0.24908098]
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   0.19869919]]
Progress: 11.7% ... Training loss: 0.272 ... Validation loss: 0.437[[ 0.33711289]
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  -0.24841459]
 [ 0.05481663 -0.02752319 -0.0751285  ...,  0.0388875   0.34703754
   0.19751803]]
Progress: 11.7% ... Training loss: 0.268 ... Validation loss: 0.436[[ 0.33819464]
 [-0.28981275]
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[[ 0.0556665  -0.15490452  0.05383736 ..., -0.14507248  0.18410867
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  -0.2496402 ]
 [ 0.05456286 -0.02725321 -0.07445437 ...,  0.03897931  0.34685817
   0.19816632]]
Progress: 11.7% ... Training loss: 0.270 ... Validation loss: 0.437[[ 0.3361799 ]
 [-0.29250476]
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  -0.24885735]
 [ 0.05451653 -0.02718752 -0.07433584 ...,  0.03899627  0.34681994
   0.19827822]]
Progress: 11.7% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.33233786]
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[[ 0.05571259 -0.15497975  0.05388571 ..., -0.1451253   0.18407218
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 [ 0.05473198 -0.02737369 -0.07484142 ...,  0.03893669  0.34724991
   0.1977367 ]]
Progress: 11.7% ... Training loss: 0.270 ... Validation loss: 0.435[[ 0.32974065]
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[[ 0.05489213 -0.15424233  0.05584057 ..., -0.14487183  0.1822607
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 [ 0.05490091 -0.02755114 -0.0752483  ...,  0.03887289  0.34784567
   0.19736992]]
Progress: 11.7% ... Training loss: 0.277 ... Validation loss: 0.443[[ 0.3476523 ]
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[[ 0.05634344 -0.15552145  0.05255808 ..., -0.14533247  0.18567171
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   0.19613993]]
Progress: 11.7% ... Training loss: 0.290 ... Validation loss: 0.464[[ 0.33311238]
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[[ 0.05476975 -0.1542131   0.05596219 ..., -0.14492763  0.18197106
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 [ 0.05484689 -0.02753343 -0.07526134 ...,  0.03885989  0.34790706
   0.19717168]]
Progress: 11.7% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.33939497]
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[[ 0.05581119 -0.15519746  0.05358373 ..., -0.1452619   0.18451507
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 [-0.18948459 -0.19128493 -0.127435   ...,  0.10221378 -0.07318536
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   0.19667195]]
Progress: 11.7% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.33740086]
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[[ 0.05570631 -0.15509436  0.05390895 ..., -0.14522539  0.18436809
  -0.1999881 ]
 [ 0.04163403  0.04562732  0.10515547 ..., -0.24519458 -0.02690146
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 ..., 
 [-0.18934039 -0.19140721 -0.12773842 ...,  0.10217059 -0.07283156
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  -0.24863884]
 [ 0.05502885 -0.02771373 -0.07568578 ...,  0.03880121  0.34851206
   0.19667631]]
Progress: 11.7% ... Training loss: 0.268 ... Validation loss: 0.436[[ 0.33276133]
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[[ 0.05573827 -0.15508496  0.05390024 ..., -0.1452235   0.18461032
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   0.19788764]]
Progress: 11.7% ... Training loss: 0.271 ... Validation loss: 0.436[[ 0.34172285]
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[[ 0.05616645 -0.15544375  0.05298768 ..., -0.14534253  0.18563729
  -0.2008163 ]
 [ 0.04175296  0.04551268  0.10488496 ..., -0.24523189 -0.02659441
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  -0.24751034]
 [ 0.05525031 -0.02788732 -0.0761362  ...,  0.03873321  0.34965134
   0.19605438]]
Progress: 11.7% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.33516726]
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[[ 0.05548358 -0.1548532   0.05447031 ..., -0.1451606   0.18394159
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 [ 0.05499798 -0.02764913 -0.07555224 ...,  0.03880487  0.34916379
   0.19671514]]
Progress: 11.7% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.33554402]
 [-0.29896607]
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[[ 0.05502003 -0.15442399  0.05554635 ..., -0.14501098  0.18299584
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   0.19660205]]
Progress: 11.7% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.34874286]
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[[ 0.05603612 -0.15534904  0.05321299 ..., -0.14529029  0.18517888
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   0.19531952]]
Progress: 11.7% ... Training loss: 0.283 ... Validation loss: 0.455[[ 0.33240074]
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[[ 0.05477218 -0.15425155  0.05602279 ..., -0.1449529   0.18235222
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  -0.24606904]
 [ 0.05520608 -0.02784137 -0.07625788 ...,  0.03873963  0.3500821
   0.19602132]]
Progress: 11.8% ... Training loss: 0.275 ... Validation loss: 0.438[[ 0.33268604]
 [-0.30035198]
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[[ 0.05406789 -0.15360354  0.05766484 ..., -0.144743    0.18086856
  -0.19646762]
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  -0.24625888]
 [ 0.0551772  -0.02781602 -0.07619059 ...,  0.03874526  0.35001262
   0.19607806]]
Progress: 11.8% ... Training loss: 0.274 ... Validation loss: 0.438[[ 0.33764943]
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[[ 0.05414234 -0.15369954  0.05751147 ..., -0.14477967  0.18120752
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  -0.2461476 ]
 [ 0.0552978  -0.02792196 -0.07651105 ...,  0.03870661  0.35052301
   0.19567885]]
Progress: 11.8% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.33839936]
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[[ 0.05418903 -0.15374551  0.05749278 ..., -0.14480065  0.1813401
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  -0.2462896 ]
 [ 0.0549895  -0.02763093 -0.07581075 ...,  0.03880406  0.34994798
   0.19633296]]
Progress: 11.8% ... Training loss: 0.268 ... Validation loss: 0.436[[ 0.33564556]
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[[ 0.05336382 -0.15303537  0.05943478 ..., -0.14454354  0.17925209
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 [ 0.0546082  -0.0272848  -0.07488804 ...,  0.03891579  0.34926531
   0.19723526]]
Progress: 11.8% ... Training loss: 0.275 ... Validation loss: 0.444[[ 0.35222345]
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[[ 0.0548239  -0.15438205  0.05607922 ..., -0.14500467  0.18265032
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   0.19498342]]
Progress: 11.8% ... Training loss: 0.284 ... Validation loss: 0.461[[ 0.33049518]
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[[ 0.05263243 -0.15259611  0.06081709 ..., -0.14442586  0.17742272
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 [ 0.05538544 -0.0279845  -0.07684574 ...,  0.03866999  0.35174606
   0.19531319]]
Progress: 11.8% ... Training loss: 0.296 ... Validation loss: 0.461[[ 0.34718344]
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[[ 0.05394133 -0.15380292  0.05762916 ..., -0.14486799  0.18094189
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 [ 0.05546076 -0.02804403 -0.07703446 ...,  0.03864818  0.35197701
   0.19508883]]
Progress: 11.8% ... Training loss: 0.273 ... Validation loss: 0.449[[ 0.33762089]
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[[ 0.05345697 -0.15339397  0.05888173 ..., -0.14474119  0.17992312
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  -0.24585761]
 [ 0.0547769  -0.02744604 -0.07541936 ...,  0.03884477  0.35080578
   0.19677067]]
Progress: 11.8% ... Training loss: 0.273 ... Validation loss: 0.445[[ 0.34947422]
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[[ 0.05459161 -0.15441813  0.05625851 ..., -0.14509118  0.18256664
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 [-0.18948005 -0.19141563 -0.12767806 ...,  0.10211328 -0.07390802
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  -0.24589482]
 [ 0.0550405  -0.02767399 -0.07599514 ...,  0.03876812  0.35148252
   0.19609701]]
Progress: 11.8% ... Training loss: 0.279 ... Validation loss: 0.456[[ 0.34718804]
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[[ 0.05504705 -0.15479937  0.05520657 ..., -0.14521762  0.18355384
  -0.19856878]
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 [-0.1900507  -0.1909531  -0.12644996 ...,  0.10226651 -0.0752626
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  -0.2463461 ]
 [ 0.05491304 -0.02753212 -0.0756954  ...,  0.038815    0.35137311
   0.19644741]]
Progress: 11.8% ... Training loss: 0.275 ... Validation loss: 0.448[[ 0.33486515]
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[[ 0.05390067 -0.15384487  0.05777408 ..., -0.1448996   0.18072941
  -0.195887  ]
 [ 0.04251117  0.04481811  0.10289911 ..., -0.24546762 -0.02447174
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 [-0.19015144 -0.19086495 -0.12627214 ...,  0.10229439 -0.07556244
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  -0.24558473]
 [ 0.05519142 -0.02776738 -0.0762948  ...,  0.03874195  0.35205764
   0.19591462]]
Progress: 11.8% ... Training loss: 0.276 ... Validation loss: 0.444[[ 0.3483155 ]
 [-0.29064474]
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[[ 0.05467867 -0.15454071  0.05616456 ..., -0.14513701  0.18285012
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   0.19530822]]
Progress: 11.8% ... Training loss: 0.276 ... Validation loss: 0.454[[ 0.33112149]
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[[ 0.05230923 -0.15253763  0.06149879 ..., -0.14450215  0.17717619
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   0.19556458]]
Progress: 11.8% ... Training loss: 0.293 ... Validation loss: 0.456[[ 0.35708929]
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  -0.2460792 ]
 [ 0.0555834  -0.02813887 -0.07721386 ...,  0.03861671  0.35351155
   0.19493443]]
Progress: 11.8% ... Training loss: 0.301 ... Validation loss: 0.494[[ 0.32560205]
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 [ 0.05545915 -0.02803155 -0.07696244 ...,  0.03864917  0.35344419
   0.19517613]]
Progress: 11.9% ... Training loss: 0.323 ... Validation loss: 0.479[[ 0.34879412]
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   0.19455099]]
Progress: 11.9% ... Training loss: 0.275 ... Validation loss: 0.455[[ 0.33310559]
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[[ 0.05200667 -0.15273353  0.06149359 ..., -0.14472027  0.17674338
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   0.19520608]]
Progress: 11.9% ... Training loss: 0.280 ... Validation loss: 0.448[[ 0.35235152]
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[[ 0.05326447 -0.1538669   0.05866964 ..., -0.14511583  0.17951549
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   0.19307294]]
Progress: 11.9% ... Training loss: 0.289 ... Validation loss: 0.473[[ 0.34381221]
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   0.19236367]]
Progress: 11.9% ... Training loss: 0.268 ... Validation loss: 0.444[[ 0.34838402]
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[[ 0.05315074 -0.15376717  0.05910544 ..., -0.14506346  0.17924058
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   0.19295347]]
Progress: 11.9% ... Training loss: 0.275 ... Validation loss: 0.455[[ 0.34861616]
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[[ 0.05397151 -0.15446274  0.05745869 ..., -0.14527898  0.18117402
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   0.19145792]]
Progress: 11.9% ... Training loss: 0.277 ... Validation loss: 0.453[[ 0.33678247]
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[[ 0.05380228 -0.15430614  0.05786511 ..., -0.1452267   0.18068295
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   0.19226381]]
Progress: 11.9% ... Training loss: 0.270 ... Validation loss: 0.438[[ 0.34988668]
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[[ 0.05525027 -0.15562867  0.0545588  ..., -0.1456735   0.18423752
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 [ 0.05720259 -0.02950028 -0.08102021 ...,  0.03815769  0.35961155
   0.19111055]]
Progress: 11.9% ... Training loss: 0.284 ... Validation loss: 0.455[[ 0.33925021]
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[[ 0.05449325 -0.15500997  0.05626809 ..., -0.14545168  0.18237161
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 [ 0.05695169 -0.02925582 -0.08048227 ...,  0.03823462  0.35935666
   0.19161962]]
Progress: 11.9% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.33173328]
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[[ 0.05319738 -0.15386563  0.05919884 ..., -0.14503773  0.17941305
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  -0.2449535 ]
 [ 0.05642418 -0.0287665  -0.07916981 ...,  0.03840777  0.35829783
   0.19291824]]
Progress: 11.9% ... Training loss: 0.286 ... Validation loss: 0.450[[ 0.34008956]
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[[ 0.0545941  -0.15513152  0.05598948 ..., -0.14547566  0.18320716
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   0.19329677]]
Progress: 11.9% ... Training loss: 0.269 ... Validation loss: 0.432[[ 0.34142983]
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   0.19125904]]
Progress: 11.9% ... Training loss: 0.268 ... Validation loss: 0.433[[ 0.33939482]
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   0.19184443]]
Progress: 11.9% ... Training loss: 0.268 ... Validation loss: 0.436[[ 0.33152372]
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   0.19147827]]
Progress: 11.9% ... Training loss: 0.280 ... Validation loss: 0.448[[ 0.34803929]
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   0.19030548]]
Progress: 12.0% ... Training loss: 0.278 ... Validation loss: 0.450[[ 0.3431911 ]
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   0.19091548]]
Progress: 12.0% ... Training loss: 0.269 ... Validation loss: 0.437[[ 0.33131195]
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[[ 0.05381391 -0.15447928  0.0581689  ..., -0.14527868  0.18132079
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   0.1928611 ]]
Progress: 12.0% ... Training loss: 0.279 ... Validation loss: 0.444[[ 0.35079989]
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   0.19082638]]
Progress: 12.0% ... Training loss: 0.287 ... Validation loss: 0.457[[ 0.3367503 ]
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   0.19291819]]
Progress: 12.0% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.34355193]
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   0.192931  ]]
Progress: 12.0% ... Training loss: 0.269 ... Validation loss: 0.437[[ 0.34048878]
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 [ 0.05597412 -0.02834324 -0.07843905 ...,  0.03852345  0.35940398
   0.192856  ]]
Progress: 12.0% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.35288914]
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[[ 0.05447526 -0.15511542  0.0568536  ..., -0.14554056  0.18301663
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   0.19076902]]
Progress: 12.0% ... Training loss: 0.293 ... Validation loss: 0.466[[ 0.33086083]
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   0.19178385]]
Progress: 12.0% ... Training loss: 0.280 ... Validation loss: 0.440[[ 0.34088728]
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   0.19262246]]
Progress: 12.0% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.34091954]
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[[ 0.05309506 -0.15402952  0.06007445 ..., -0.14519746  0.17933377
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   0.19244829]]
Progress: 12.0% ... Training loss: 0.266 ... Validation loss: 0.438[[ 0.35051791]
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[[ 0.05425007 -0.1550496   0.05742611 ..., -0.14553521  0.18230375
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 [ 0.04160285  0.04557804  0.10466929 ..., -0.2452307  -0.02609759
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   0.19106101]]
Progress: 12.0% ... Training loss: 0.283 ... Validation loss: 0.462[[ 0.33583492]
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[[ 0.0534319  -0.15436259  0.05916628 ..., -0.14532715  0.18042487
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   0.19154006]]
Progress: 12.0% ... Training loss: 0.269 ... Validation loss: 0.434[[ 0.34605324]
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[[ 0.05402519 -0.15490499  0.05783845 ..., -0.14551014  0.1818093
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   0.19004938]]
Progress: 12.0% ... Training loss: 0.273 ... Validation loss: 0.445[[ 0.33793626]
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[[ 0.05335852 -0.15433809  0.05940923 ..., -0.14530522  0.18007751
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   0.18908781]]
Progress: 12.0% ... Training loss: 0.268 ... Validation loss: 0.437[[ 0.33942639]
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[[ 0.05324393 -0.15420774  0.05964568 ..., -0.1452609   0.17984728
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   0.18849515]]
Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.437[[ 0.34112682]
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[[ 0.05270673 -0.15376037  0.06088906 ..., -0.14510436  0.17876754
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   0.18800609]]
Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.439[[ 0.35315929]
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   0.18642589]]
Progress: 12.1% ... Training loss: 0.293 ... Validation loss: 0.470[[ 0.33192204]
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   0.18885801]]
Progress: 12.1% ... Training loss: 0.278 ... Validation loss: 0.441[[ 0.33363805]
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[[ 0.05275963 -0.15386467  0.06086221 ..., -0.1451637   0.17900662
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   0.18860675]]
Progress: 12.1% ... Training loss: 0.273 ... Validation loss: 0.439[[ 0.35189426]
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[[ 0.05430576 -0.15527165  0.05722516 ..., -0.14563792  0.18271183
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   0.18703007]]
Progress: 12.1% ... Training loss: 0.292 ... Validation loss: 0.468[[ 0.33132579]
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[[ 0.05320093 -0.1543567   0.05961593 ..., -0.14535421  0.18001427
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   0.18803463]]
Progress: 12.1% ... Training loss: 0.282 ... Validation loss: 0.445[[ 0.34170936]
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[[ 0.05375169 -0.15482704  0.05842862 ..., -0.14554117  0.18152962
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   0.18770551]]
Progress: 12.1% ... Training loss: 0.268 ... Validation loss: 0.445[[ 0.34187928]
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[[ 0.05372909 -0.15482576  0.05844248 ..., -0.14553044  0.18149614
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   0.18756833]]
Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.443[[ 0.33528302]
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[[ 0.05333989 -0.15450506  0.05938069 ..., -0.14540584  0.18078155
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   0.18878643]]
Progress: 12.1% ... Training loss: 0.271 ... Validation loss: 0.441[[ 0.34060927]
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[[ 0.05438735 -0.15544087  0.05697855 ..., -0.14574695  0.18323227
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 [ 0.05740495 -0.02952193 -0.08167773 ...,  0.03807833  0.36535612
   0.18879172]]
Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.441[[ 0.33973697]
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[[ 0.05433574 -0.15542681  0.05711683 ..., -0.14573495  0.18294967
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Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.441[[ 0.34089903]
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   0.1894302 ]]
Progress: 12.1% ... Training loss: 0.268 ... Validation loss: 0.446[[ 0.34121545]
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 [ 0.05734604 -0.02943093 -0.08154691 ...,  0.03811239  0.36558872
   0.18903712]]
Progress: 12.1% ... Training loss: 0.268 ... Validation loss: 0.444[[ 0.34071039]
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   0.18928955]]
Progress: 12.1% ... Training loss: 0.267 ... Validation loss: 0.442[[ 0.33255864]
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   0.19025941]]
Progress: 12.2% ... Training loss: 0.274 ... Validation loss: 0.440[[ 0.34794322]
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   0.18915664]]
Progress: 12.2% ... Training loss: 0.280 ... Validation loss: 0.458[[ 0.33253867]
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[[ 0.05317112 -0.15449168  0.05978541 ..., -0.14547673  0.18041742
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   0.19020446]]
Progress: 12.2% ... Training loss: 0.277 ... Validation loss: 0.443[[ 0.33717445]
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   0.18912883]]
Progress: 12.2% ... Training loss: 0.267 ... Validation loss: 0.436[[ 0.3412618 ]
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 [ 0.05702918 -0.02915352 -0.08107675 ...,  0.03822047  0.36600972
   0.18937054]]
Progress: 12.2% ... Training loss: 0.267 ... Validation loss: 0.438[[ 0.3374286 ]
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[[ 0.05320705 -0.15448817  0.05988602 ..., -0.1454826   0.18067289
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   0.18930649]]
Progress: 12.2% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.34190797]
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[[ 0.05372013 -0.1549556   0.05873653 ..., -0.14563657  0.181785   -0.1953152 ]
 [ 0.04202074  0.045212    0.10343682 ..., -0.24536416 -0.02443232
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   0.18773503]]
Progress: 12.2% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.34670484]
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[[ 0.05448659 -0.15563193  0.05707121 ..., -0.14586018  0.18359088
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   0.18763333]]
Progress: 12.2% ... Training loss: 0.277 ... Validation loss: 0.442[[ 0.33043089]
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[[ 0.05347389 -0.15475528  0.05937968 ..., -0.14556077  0.18121069
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   0.18822945]]
Progress: 12.2% ... Training loss: 0.280 ... Validation loss: 0.440[[ 0.34166492]
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[[ 0.05355781 -0.15485455  0.05923001 ..., -0.14559757  0.18145561
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   0.18759201]]
Progress: 12.2% ... Training loss: 0.266 ... Validation loss: 0.435[[ 0.33494601]
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[[ 0.05274241 -0.15412238  0.06107765 ..., -0.14533436  0.17990875
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   0.18790402]]
Progress: 12.2% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.33969926]
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Progress: 12.2% ... Training loss: 0.267 ... Validation loss: 0.434[[ 0.33350804]
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 [ 0.05784633 -0.02978363 -0.0829824  ...,  0.03801144  0.36910911
   0.18722119]]
Progress: 12.2% ... Training loss: 0.273 ... Validation loss: 0.437[[ 0.33944864]
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   0.18806489]]
Progress: 12.2% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.33415243]
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   0.18836287]]
Progress: 12.2% ... Training loss: 0.271 ... Validation loss: 0.434[[ 0.34006507]
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   0.18822313]]
Progress: 12.3% ... Training loss: 0.267 ... Validation loss: 0.432[[ 0.34649428]
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   0.18718502]]
Progress: 12.3% ... Training loss: 0.276 ... Validation loss: 0.439[[ 0.34010812]
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   0.18741269]]
Progress: 12.3% ... Training loss: 0.268 ... Validation loss: 0.429[[ 0.34145334]
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   0.1878075 ]]
Progress: 12.3% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.34817592]
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   0.18727063]]
Progress: 12.3% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.34263667]
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   0.1875464 ]]
Progress: 12.3% ... Training loss: 0.266 ... Validation loss: 0.435[[ 0.3370711 ]
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[[ 0.05324464 -0.15461259  0.06014634 ..., -0.14554944  0.18205818
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 [ 0.05717289 -0.02906144 -0.08140776 ...,  0.03823058  0.3687976
   0.1878924 ]]
Progress: 12.3% ... Training loss: 0.272 ... Validation loss: 0.438[[ 0.35329244]
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[[ 0.05454294 -0.15578284  0.05725409 ..., -0.14596607  0.18515317
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 [ 0.0574901  -0.02932493 -0.08207835 ...,  0.03813791  0.36952709
   0.18704127]]
Progress: 12.3% ... Training loss: 0.281 ... Validation loss: 0.454[[ 0.33825787]
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[[ 0.05342562 -0.15486852  0.05969853 ..., -0.14564306  0.18257874
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   0.18750329]]
Progress: 12.3% ... Training loss: 0.272 ... Validation loss: 0.438[[ 0.33820422]
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[[ 0.05317906 -0.1546862   0.06023622 ..., -0.14557271  0.18208854
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   0.18833739]]
Progress: 12.3% ... Training loss: 0.272 ... Validation loss: 0.440[[ 0.34506927]
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[[ 0.05403346 -0.15543451  0.05828144 ..., -0.14581875  0.18407216
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   0.18777745]]
Progress: 12.3% ... Training loss: 0.266 ... Validation loss: 0.438[[ 0.33895715]
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   0.18724711]]
Progress: 12.3% ... Training loss: 0.269 ... Validation loss: 0.437[[ 0.34147488]
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   0.18834524]]
Progress: 12.3% ... Training loss: 0.267 ... Validation loss: 0.439[[ 0.35356746]
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   0.18585962]]
Progress: 12.3% ... Training loss: 0.287 ... Validation loss: 0.472[[ 0.34426576]
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   0.18606081]]
Progress: 12.3% ... Training loss: 0.266 ... Validation loss: 0.440[[ 0.34436651]
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   0.18715896]]
Progress: 12.4% ... Training loss: 0.267 ... Validation loss: 0.443[[ 0.34472128]
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   0.18484569]]
Progress: 12.4% ... Training loss: 0.268 ... Validation loss: 0.444[[ 0.34666317]
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   0.18423293]]
Progress: 12.4% ... Training loss: 0.272 ... Validation loss: 0.448[[ 0.33766611]
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   0.18419967]]
Progress: 12.4% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.34599632]
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   0.18321868]]
Progress: 12.4% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.34428515]
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   0.18337573]]
Progress: 12.4% ... Training loss: 0.267 ... Validation loss: 0.437[[ 0.34683543]
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[[ 0.05529549 -0.15645229  0.0555578  ..., -0.14621812  0.18775694
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   0.18248612]]
Progress: 12.4% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.33765641]
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[[ 0.05418582 -0.15550201  0.05818537 ..., -0.14588569  0.18533583
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   0.18185238]]
Progress: 12.4% ... Training loss: 0.270 ... Validation loss: 0.434[[ 0.33489755]
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[[ 0.05362445 -0.15500748  0.05959622 ..., -0.14571118  0.18394839
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   0.18190186]]
Progress: 12.4% ... Training loss: 0.278 ... Validation loss: 0.439[[ 0.35214485]
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[[ 0.05487186 -0.15609753  0.05678521 ..., -0.1461417   0.1873808
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   0.18282075]]
Progress: 12.4% ... Training loss: 0.279 ... Validation loss: 0.459[[ 0.33848073]
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[[ 0.05436503 -0.15567486  0.05799684 ..., -0.14600207  0.18615184
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   0.18301868]]
Progress: 12.4% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.33949985]
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[[ 0.05450371 -0.15577086  0.05773363 ..., -0.14602425  0.18654968
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   0.18376582]]
Progress: 12.4% ... Training loss: 0.266 ... Validation loss: 0.435[[ 0.34245143]
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   0.18370126]]
Progress: 12.4% ... Training loss: 0.265 ... Validation loss: 0.438[[ 0.34551379]
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   0.18194138]]
Progress: 12.4% ... Training loss: 0.267 ... Validation loss: 0.441[[ 0.34338789]
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   0.18293843]]
Progress: 12.4% ... Training loss: 0.266 ... Validation loss: 0.437[[ 0.33928358]
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[[ 0.05350708 -0.15490955  0.06006918 ..., -0.14574055  0.18433901
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   0.18381899]]
Progress: 12.5% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.33179938]
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   0.18440512]]
Progress: 12.5% ... Training loss: 0.274 ... Validation loss: 0.437[[ 0.3435071 ]
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   0.18511362]]
Progress: 12.5% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.33322103]
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[[ 0.05344028 -0.1548915   0.06021261 ..., -0.14574058  0.1844281
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   0.18725487]]
Progress: 12.5% ... Training loss: 0.270 ... Validation loss: 0.435[[ 0.3477344 ]
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[[ 0.05481552 -0.1561479   0.05698376 ..., -0.14619558  0.18798384
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   0.1856812 ]]
Progress: 12.5% ... Training loss: 0.281 ... Validation loss: 0.447[[ 0.32904597]
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[[ 0.05317203 -0.15478204  0.06070545 ..., -0.14575583  0.18379126
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   0.18701375]]
Progress: 12.5% ... Training loss: 0.282 ... Validation loss: 0.446[[ 0.34038082]
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[[ 0.05389872 -0.15545736  0.05892242 ..., -0.1460047   0.18571885
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   0.18750724]]
Progress: 12.5% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.33616311]
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[[ 0.05332255 -0.15496598  0.06023104 ..., -0.14582268  0.18441027
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   0.18941913]]
Progress: 12.5% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.33289394]
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[[ 0.05298618 -0.1546469   0.06111293 ..., -0.14571394  0.18379109
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 [ 0.0554974  -0.02726739 -0.07756017 ...,  0.03884302  0.37002859
   0.19017533]]
Progress: 12.5% ... Training loss: 0.273 ... Validation loss: 0.438[[ 0.34948877]
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[[ 0.05382635 -0.15544605  0.0591952  ..., -0.14601385  0.18598083
  -0.1947021 ]
 [ 0.0403595   0.04659472  0.10656342 ..., -0.24495191 -0.02689503
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   0.18980455]]
Progress: 12.5% ... Training loss: 0.280 ... Validation loss: 0.456[[ 0.34000638]
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[[ 0.05330477 -0.15497493  0.06035127 ..., -0.14587037  0.18487802
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   0.18949425]]
Progress: 12.5% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.35445208]
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[[ 0.05470161 -0.15620241  0.05720182 ..., -0.14629346  0.18832021
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   0.18861899]]
Progress: 12.5% ... Training loss: 0.301 ... Validation loss: 0.480[[ 0.32636854]
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[[ 0.05281613 -0.15472568  0.06135181 ..., -0.14581571  0.18373294
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 [ 0.05537524 -0.02713086 -0.07746195 ...,  0.03887358  0.37077     0.19010358]]
Progress: 12.5% ... Training loss: 0.300 ... Validation loss: 0.458[[ 0.35629199]
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[[ 0.05503252 -0.15684563  0.05608589 ..., -0.14663058  0.18960332
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  -0.24434547]
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   0.18941899]]
Progress: 12.5% ... Training loss: 0.306 ... Validation loss: 0.490[[ 0.33224595]
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[[ 0.05309135 -0.15525384  0.06036342 ..., -0.14611183  0.18485859
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   0.19100312]]
Progress: 12.5% ... Training loss: 0.278 ... Validation loss: 0.440[[ 0.34391433]
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[[ 0.05377782 -0.15590211  0.0587009  ..., -0.14634027  0.18660009
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   0.18873151]]
Progress: 12.6% ... Training loss: 0.267 ... Validation loss: 0.439[[ 0.34383255]
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[[ 0.05412828 -0.1561713   0.05796825 ..., -0.14643984  0.18738155
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   0.18931958]]
Progress: 12.6% ... Training loss: 0.266 ... Validation loss: 0.439[[ 0.34262331]
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[[ 0.05408477 -0.15611434  0.05810173 ..., -0.14641188  0.18755865
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   0.18927607]]
Progress: 12.6% ... Training loss: 0.266 ... Validation loss: 0.437[[ 0.34107365]
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 [ 0.05514502 -0.02694756 -0.0772668  ...,  0.0389286   0.37167699
   0.19028188]]
Progress: 12.6% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.3540503 ]
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[[ 0.0552405  -0.15712195  0.05547869 ..., -0.14677894  0.19052353
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 [ 0.05569138 -0.02742177 -0.07855209 ...,  0.03876501  0.37317731
   0.18891001]]
Progress: 12.6% ... Training loss: 0.298 ... Validation loss: 0.470[[ 0.33037078]
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[[ 0.05371847 -0.15590195  0.05886659 ..., -0.14638071  0.18660617
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   0.18921269]]
Progress: 12.6% ... Training loss: 0.286 ... Validation loss: 0.444[[ 0.34497329]
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[[ 0.05528776 -0.15735433  0.05524984 ..., -0.14692739  0.1905726
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  -0.245421  ]
 [ 0.05588818 -0.02760451 -0.0790703  ...,  0.03868844  0.37396209
   0.18844831]]
Progress: 12.6% ... Training loss: 0.268 ... Validation loss: 0.437[[ 0.34056173]
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[[ 0.05510972 -0.15720397  0.05565072 ..., -0.14688678  0.19020815
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 [ 0.05562011 -0.02736241 -0.07840028 ...,  0.03877751  0.37345261
   0.18909583]]
Progress: 12.6% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.3446402 ]
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[[ 0.05628822 -0.15827559  0.05295814 ..., -0.14725037  0.19290146
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 [ 0.0552842  -0.0270555  -0.07770342 ...,  0.03888523  0.37270195
   0.18989526]]
Progress: 12.6% ... Training loss: 0.267 ... Validation loss: 0.439[[ 0.34218301]
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[[ 0.05594113 -0.15796049  0.05371573 ..., -0.1471532   0.19223315
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 [ 0.05519849 -0.02695784 -0.07750845 ...,  0.03890982  0.37255392
   0.1900287 ]]
Progress: 12.6% ... Training loss: 0.265 ... Validation loss: 0.434[[ 0.34089525]
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   0.18859456]]
Progress: 12.6% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.34104606]
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[[ 0.05509087 -0.15724009  0.05554032 ..., -0.14690462  0.19036157
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   0.18897847]]
Progress: 12.6% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.33880586]
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[[ 0.05476242 -0.15691868  0.05636234 ..., -0.14679721  0.18986104
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   0.19039054]]
Progress: 12.6% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.34799871]
 [-0.29051381]
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[[ 0.05593023 -0.1579669   0.05361798 ..., -0.14718561  0.19279383
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 [ 0.05568785 -0.02736114 -0.07870443 ...,  0.03876651  0.37444606
   0.18856347]]
Progress: 12.6% ... Training loss: 0.273 ... Validation loss: 0.440[[ 0.33537055]
 [-0.30217785]
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[[ 0.05449038 -0.15672774  0.0569113  ..., -0.14673745  0.18959754
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   0.18981491]]
Progress: 12.6% ... Training loss: 0.274 ... Validation loss: 0.435[[ 0.35713572]
 [-0.28262809]
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[[ 0.05675626 -0.15873956  0.05173236 ..., -0.14747786  0.1952816
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 [-0.19116904 -0.19091286 -0.125185   ...,  0.10198616 -0.08106005
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   0.18804749]]
Progress: 12.7% ... Training loss: 0.311 ... Validation loss: 0.473[[ 0.32692572]
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[[ 0.05381658 -0.15638163  0.05805807 ..., -0.1467234   0.1885094  -0.195956  ]
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   0.18967699]]
Progress: 12.7% ... Training loss: 0.308 ... Validation loss: 0.465[[ 0.35111321]
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 [ 0.05631206 -0.02802748 -0.0805156  ...,  0.03849735  0.37674688
   0.18710952]]
Progress: 12.7% ... Training loss: 0.276 ... Validation loss: 0.448[[ 0.3397434 ]
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[[ 0.053544   -0.15629794  0.05840716 ..., -0.14676149  0.18812276
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   0.18710661]]
Progress: 12.7% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.33861577]
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[[ 0.05363973 -0.15638043  0.05826201 ..., -0.14678596  0.1881862
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   0.18599532]]
Progress: 12.7% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.34277454]
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[[ 0.05435942 -0.1570065   0.05664287 ..., -0.14700392  0.18999497
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 [ 0.05716579 -0.02875709 -0.0824306  ...,  0.03822377  0.37913376
   0.18495751]]
Progress: 12.7% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.33353753]
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[[ 0.05366864 -0.15640094  0.05823833 ..., -0.14678846  0.18819907
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 [ 0.05598443 -0.02771096 -0.07979662 ...,  0.03859074  0.37655003
   0.18754075]]
Progress: 12.7% ... Training loss: 0.278 ... Validation loss: 0.441[[ 0.34820227]
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[[ 0.05482534 -0.15745981  0.05559688 ..., -0.14719316  0.19108893
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 [ 0.05622468 -0.0279525  -0.08034976 ...,  0.03850068  0.37713036
   0.18696302]]
Progress: 12.7% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.33822637]
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[[ 0.05322958 -0.15608462  0.05930507 ..., -0.14673049  0.18741118
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 [-0.19120809 -0.19101262 -0.12528683 ...,  0.10189024 -0.08116    -0.04528277]
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  -0.24779451]
 [ 0.05605724 -0.02777808 -0.07995551 ...,  0.0385593   0.37718865
   0.18735761]]
Progress: 12.7% ... Training loss: 0.267 ... Validation loss: 0.432[[ 0.35246303]
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[[ 0.05464913 -0.15736689  0.056138   ..., -0.14719226  0.19086693
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 [-0.19091601 -0.19127449 -0.12590416 ...,  0.10179254 -0.08044459
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   0.1860439 ]]
Progress: 12.7% ... Training loss: 0.285 ... Validation loss: 0.450[[ 0.34034306]
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[[ 0.05413529 -0.15693533  0.05721953 ..., -0.14706675  0.18973439
  -0.19696455]
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  -0.24742146]
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   0.18702777]]
Progress: 12.7% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.34222833]
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 [ 0.39206883]
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[[ 0.05421297 -0.15704085  0.05714634 ..., -0.14707627  0.189973
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  -0.24673317]
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   0.18677731]]
Progress: 12.7% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.35253693]
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[[ 0.05493365 -0.15767269  0.0555569  ..., -0.14730767  0.1914965
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  -0.24656392]
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   0.18470639]]
Progress: 12.7% ... Training loss: 0.278 ... Validation loss: 0.450[[ 0.33999804]
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[[ 0.05432051 -0.15716395  0.05684695 ..., -0.14713721  0.1901884
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  -0.24601864]
 [ 0.05648814 -0.02815157 -0.08118425 ...,  0.03841371  0.37902143
   0.18608032]]
Progress: 12.7% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.34012346]
 [-0.29952835]
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[[ 0.05397495 -0.15682974  0.05768378 ..., -0.14703501  0.18942393
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 [ 0.05649728 -0.02815951 -0.08126512 ...,  0.03840166  0.37905378
   0.1859641 ]]
Progress: 12.7% ... Training loss: 0.267 ... Validation loss: 0.431[[ 0.3367467 ]
 [-0.30211049]
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[[ 0.05319346 -0.15611852  0.05955314 ..., -0.14678724  0.18741963
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  -0.24739024]
 [ 0.05649572 -0.02816054 -0.08124761 ...,  0.03839689  0.37923465
   0.18595718]]
Progress: 12.8% ... Training loss: 0.274 ... Validation loss: 0.438[[ 0.3421309 ]
 [-0.29619195]
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 [ 1.54307124]
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[[ 0.0528675  -0.15578502  0.06056885 ..., -0.14666757  0.1866605
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  -0.24831888]
 [ 0.05623955 -0.02791424 -0.08064322 ...,  0.03848467  0.37880896
   0.18648635]]
Progress: 12.8% ... Training loss: 0.267 ... Validation loss: 0.437[[ 0.34716068]
 [-0.29156339]
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[[ 0.05391001 -0.15670137  0.05825318 ..., -0.14699106  0.18930064
  -0.1960772 ]
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 [ 0.05712604 -0.02867027 -0.08266409 ...,  0.03821683  0.38120669
   0.18441427]]
Progress: 12.8% ... Training loss: 0.269 ... Validation loss: 0.442[[ 0.34276025]
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[[ 0.05368884 -0.1565175   0.05879193 ..., -0.14692453  0.18859318
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  -0.24846365]
 [ 0.05719603 -0.02873817 -0.08281954 ...,  0.03819656  0.38150331
   0.18416468]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.35008442]
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[[ 0.05463958 -0.15737887  0.05669258 ..., -0.14720504  0.1907798
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  -0.24909144]
 [ 0.05724409 -0.02876625 -0.08288197 ...,  0.03819556  0.38179592
   0.18408924]]
Progress: 12.8% ... Training loss: 0.274 ... Validation loss: 0.448[[ 0.34484898]
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[[ 0.05387943 -0.1567497   0.0584084  ..., -0.14697881  0.18884275
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 [-0.19140229 -0.19090222 -0.12496076 ...,  0.10190727 -0.08193836
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  -0.24898143]
 [ 0.0573682  -0.02886054 -0.08313938 ...,  0.03817321  0.38216244
   0.18376053]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.3444152 ]
 [-0.29355823]
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[[ 0.05390278 -0.15676555  0.05849935 ..., -0.14697707  0.18886871
  -0.19647774]
 [ 0.04065321  0.04631089  0.1056148  ..., -0.24508819 -0.02521323
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 [-0.19154041 -0.1907869  -0.1246955  ...,  0.10195161 -0.08242602
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  -0.24949471]
 [ 0.05716926 -0.02868549 -0.08262217 ...,  0.03822844  0.38191776
   0.18432945]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.437[[ 0.34792937]
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[[ 0.05478405 -0.15745298  0.05659289 ..., -0.14722589  0.19105079
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 ..., 
 [-0.1912972  -0.19097866 -0.12527166 ...,  0.10187669 -0.08176688
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  -0.25109564]
 [ 0.05716132 -0.02866524 -0.08261563 ...,  0.03823652  0.38210747
   0.18424659]]
Progress: 12.8% ... Training loss: 0.271 ... Validation loss: 0.444[[ 0.33842332]
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[[ 0.05410404 -0.15687499  0.05817619 ..., -0.14702592  0.18926367
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 [-0.19132235 -0.19095646 -0.12527214 ...,  0.10188556 -0.08178145
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  -0.25036134]
 [ 0.05731562 -0.02878946 -0.08294736 ...,  0.0381948   0.38254792
   0.18391524]]
Progress: 12.8% ... Training loss: 0.268 ... Validation loss: 0.432[[ 0.34976128]
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[[ 0.0548093  -0.1574701   0.05652752 ..., -0.147252    0.19118707
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 [ 0.04050654  0.04644503  0.1059234  ..., -0.2450417  -0.02544101
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  -0.25037992]
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   0.18145728]]
Progress: 12.8% ... Training loss: 0.277 ... Validation loss: 0.450[[ 0.34040667]
 [-0.29752163]
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[[ 0.05402182 -0.15684877  0.05837422 ..., -0.14704776  0.18928863
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   0.18159568]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.34040204]
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[[ 0.05403199 -0.15688103  0.05833573 ..., -0.14706168  0.18933471
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  -0.24915482]
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   0.18144965]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.35025848]
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[[ 0.05529132 -0.15800942  0.05542616 ..., -0.14744782  0.19236344
  -0.19994106]
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  -0.24985048]
 [ 0.05875748 -0.03003293 -0.08630721 ...,  0.03775904  0.38660257
   0.18024236]]
Progress: 12.8% ... Training loss: 0.275 ... Validation loss: 0.447[[ 0.33981917]
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 [ 0.39291961]
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[[ 0.05398954 -0.15690614  0.05829908 ..., -0.14707925  0.18910832
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  -0.2494466 ]
 [ 0.05854555 -0.02985654 -0.08585032 ...,  0.03781974  0.3861085
   0.1807386 ]]
Progress: 12.8% ... Training loss: 0.266 ... Validation loss: 0.428[[ 0.34770556]
 [-0.29015437]
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[[ 0.05511518 -0.15789021  0.05569021 ..., -0.14743895  0.19176184
  -0.1999536 ]
 [ 0.04014792  0.0467274   0.10669881 ..., -0.2449497  -0.02617828
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  -0.24930849]
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   0.18040049]]
Progress: 12.8% ... Training loss: 0.272 ... Validation loss: 0.438[[ 0.34554325]
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[[ 0.05543653 -0.15816368  0.05488556 ..., -0.14751725  0.19244097
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 [-0.19217892 -0.1902864  -0.12356944 ...,  0.10213176 -0.08408772
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 [ 0.05872169 -0.02998058 -0.08623715 ...,  0.03777955  0.3869392
   0.18033491]]
Progress: 12.9% ... Training loss: 0.269 ... Validation loss: 0.432[[ 0.35042775]
 [-0.28726536]
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[[ 0.05582096 -0.1585105   0.0539695  ..., -0.14763373  0.19382282
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   0.17894713]]
Progress: 12.9% ... Training loss: 0.282 ... Validation loss: 0.446[[ 0.3347672 ]
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[[ 0.0542753  -0.15724809  0.05739902 ..., -0.14722028  0.19004474
  -0.1982146 ]
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  -0.24853386]
 [ 0.0589087  -0.03014294 -0.08692273 ...,  0.03771982  0.38789397
   0.17944258]]
Progress: 12.9% ... Training loss: 0.274 ... Validation loss: 0.429[[ 0.33500587]
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[[ 0.05434575 -0.15727449  0.05735088 ..., -0.14724425  0.19024543
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 [ 0.05884773 -0.03009478 -0.08674828 ...,  0.03774436  0.3879425
   0.17956693]]
Progress: 12.9% ... Training loss: 0.275 ... Validation loss: 0.432[[ 0.34800059]
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[[ 0.05526301 -0.15809826  0.05528329 ..., -0.14754483  0.19257658
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 [ 0.05927945 -0.03050764 -0.08770546 ...,  0.03758991  0.38898992
   0.17834644]]
Progress: 12.9% ... Training loss: 0.272 ... Validation loss: 0.439[[ 0.3299022 ]
 [-0.30542313]
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[[ 0.05325368 -0.15639154  0.05976445 ..., -0.14698347  0.1875573
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 [-0.19207478 -0.19043854 -0.12388365 ...,  0.10205337 -0.08389623
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  -0.2477306 ]
 [ 0.05882439 -0.03010733 -0.0867051  ...,  0.03772757  0.38792028
   0.17928802]]
Progress: 12.9% ... Training loss: 0.292 ... Validation loss: 0.443[[ 0.34421789]
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[[ 0.05371236 -0.15681685  0.05870985 ..., -0.14715701  0.18885931
  -0.19716073]
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 [-0.19141    -0.19105338 -0.12541448 ...,  0.10182885 -0.08223485
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  -0.24839453]
 [ 0.05928813 -0.03054631 -0.08789259 ...,  0.03757055  0.38923766
   0.17821373]]
Progress: 12.9% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.34183131]
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[[ 0.05340621 -0.15655195  0.05939346 ..., -0.14707106  0.18794288
  -0.1965834 ]
 [ 0.03991887  0.04691349  0.10702903 ..., -0.24489138 -0.02658098
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 ..., 
 [-0.19191718 -0.19062618 -0.12437921 ...,  0.10196731 -0.08344894
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  -0.24824875]
 [ 0.05915599 -0.03042859 -0.08759945 ...,  0.03760681  0.38893041
   0.1784654 ]]
Progress: 12.9% ... Training loss: 0.265 ... Validation loss: 0.431[[ 0.34045548]
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[[ 0.05301623 -0.15623772  0.06042612 ..., -0.14693767  0.18690056
  -0.19601873]
 [ 0.04011017  0.04674792  0.10658956 ..., -0.24494911 -0.02604383
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 [-0.19187407 -0.19067475 -0.12439368 ...,  0.101961   -0.08341817
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 [ 0.0591698  -0.03044338 -0.08755196 ...,  0.0375957   0.38921471
   0.17837988]]
Progress: 12.9% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.34583069]
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[[ 0.05321636 -0.15645461  0.05999227 ..., -0.14701336  0.18733246
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   0.17863247]]
Progress: 12.9% ... Training loss: 0.265 ... Validation loss: 0.435[[ 0.34308642]
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[[ 0.05285711 -0.15610592  0.06105583 ..., -0.14690441  0.18693071
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   0.18026989]]
Progress: 12.9% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.33621273]
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   0.18064535]]
Progress: 12.9% ... Training loss: 0.273 ... Validation loss: 0.436[[ 0.33344053]
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[[ 0.05198356 -0.15530571  0.06318853 ..., -0.14661991  0.18483541
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   0.18074998]]
Progress: 12.9% ... Training loss: 0.280 ... Validation loss: 0.442[[ 0.35114443]
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   0.1801336 ]]
Progress: 12.9% ... Training loss: 0.280 ... Validation loss: 0.459[[ 0.34559765]
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[[ 0.05228392 -0.15560704  0.0625233  ..., -0.14674269  0.18597721
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   0.18100969]]
Progress: 12.9% ... Training loss: 0.266 ... Validation loss: 0.442[[ 0.34141966]
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   0.18077222]]
Progress: 13.0% ... Training loss: 0.265 ... Validation loss: 0.435[[ 0.34219834]
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   0.18095152]]
Progress: 13.0% ... Training loss: 0.265 ... Validation loss: 0.436[[ 0.34604628]
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[[ 0.05251464 -0.15578145  0.0623482  ..., -0.14680707  0.18659184
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   0.17989658]]
Progress: 13.0% ... Training loss: 0.266 ... Validation loss: 0.440[[ 0.3434104 ]
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[[ 0.05280102 -0.15602051  0.06164012 ..., -0.14689101  0.18733815
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 [ 0.05862603 -0.02984116 -0.08629322 ...,  0.03778792  0.39016731
   0.17942326]]
Progress: 13.0% ... Training loss: 0.265 ... Validation loss: 0.435[[ 0.35514404]
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[[ 0.0539046  -0.15693361  0.05920113 ..., -0.14719373  0.1902987
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  -0.24926347]
 [ 0.05852987 -0.02973662 -0.0860801  ...,  0.03782546  0.39032203
   0.17961345]]
Progress: 13.0% ... Training loss: 0.299 ... Validation loss: 0.469[[ 0.335882  ]
 [-0.29691885]
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[[ 0.05233988 -0.15572185  0.06250436 ..., -0.14679486  0.18654526
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 [-0.19217555 -0.19047811 -0.12383744 ...,  0.1019708  -0.08446407
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 [ 0.05754938 -0.02892529 -0.08391294 ...,  0.03808381  0.38822624
   0.18172647]]
Progress: 13.0% ... Training loss: 0.271 ... Validation loss: 0.433[[ 0.35194482]
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[[ 0.05350309 -0.15678167  0.05991932 ..., -0.14717204  0.18946423
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 [-0.19130898 -0.19124287 -0.12570283 ...,  0.10168387 -0.08244619
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 [ 0.05753163 -0.02891948 -0.08390236 ...,  0.03808794  0.38833734
   0.18153888]]
Progress: 13.0% ... Training loss: 0.279 ... Validation loss: 0.451[[ 0.33657175]
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[[ 0.05247288 -0.15593054  0.06219874 ..., -0.14687568  0.1869416
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 [-0.19164302 -0.19097657 -0.12493648 ...,  0.10177364 -0.08329691
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 [ 0.05730597 -0.02871558 -0.08341263 ...,  0.03815449  0.38785126
   0.18209815]]
Progress: 13.0% ... Training loss: 0.273 ... Validation loss: 0.435[[ 0.35400523]
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[[ 0.05404471 -0.1573502   0.05859921 ..., -0.14740035  0.19085847
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   0.17951877]]
Progress: 13.0% ... Training loss: 0.283 ... Validation loss: 0.458[[ 0.33577521]
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   0.17985908]]
Progress: 13.0% ... Training loss: 0.273 ... Validation loss: 0.434[[ 0.33850783]
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[[ 0.05272642 -0.15624777  0.06152627 ..., -0.14703213  0.18766343
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   0.18009569]]
Progress: 13.0% ... Training loss: 0.268 ... Validation loss: 0.431[[ 0.3488533 ]
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   0.17880247]]
Progress: 13.0% ... Training loss: 0.273 ... Validation loss: 0.450[[ 0.32551111]
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[[ 0.05126556 -0.15506304  0.06499242 ..., -0.14661316  0.18433607
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   0.1803746 ]]
Progress: 13.0% ... Training loss: 0.318 ... Validation loss: 0.467[[ 0.34910481]
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[[ 0.05256786 -0.15629298  0.06188942 ..., -0.14708513  0.18759397
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   0.17799889]]
Progress: 13.0% ... Training loss: 0.274 ... Validation loss: 0.458[[ 0.33875661]
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[[ 0.05178783 -0.1556299   0.06363776 ..., -0.14686427  0.18552504
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   0.17907281]]
Progress: 13.0% ... Training loss: 0.266 ... Validation loss: 0.437[[ 0.34044367]
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[[ 0.0517951  -0.15562119  0.06379602 ..., -0.14685356  0.1854743
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   0.17908861]]
Progress: 13.1% ... Training loss: 0.266 ... Validation loss: 0.439[[ 0.34576296]
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 [ 0.05816945 -0.02956425 -0.08578246 ...,  0.03779031  0.39192986  0.17939   ]]
Progress: 13.1% ... Training loss: 0.269 ... Validation loss: 0.448[[ 0.34169763]
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 [ 0.05785743 -0.02932203 -0.0851727  ...,  0.0378742   0.3913452
   0.18007669]]
Progress: 13.1% ... Training loss: 0.266 ... Validation loss: 0.439[[ 0.34675038]
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[[ 0.05176229 -0.15559043  0.06400082 ..., -0.14683568  0.18563717
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 [-0.19142763 -0.19131338 -0.12556    ...,  0.1016467  -0.08294812
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 [ 0.05827265 -0.02967224 -0.08611416 ...,  0.03775169  0.39240844
   0.17918368]]
Progress: 13.1% ... Training loss: 0.270 ... Validation loss: 0.451[[ 0.33337038]
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[[ 0.05193645 -0.15568681  0.06374588 ..., -0.14687475  0.18664886
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 [ 0.05708474 -0.02863687 -0.0834421  ...,  0.03810954  0.3900909
   0.18214111]]
Progress: 13.1% ... Training loss: 0.270 ... Validation loss: 0.431[[ 0.3454004 ]
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[[ 0.05305193 -0.15667279  0.06116724 ..., -0.14723652  0.18948233
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   0.18142589]]
Progress: 13.1% ... Training loss: 0.273 ... Validation loss: 0.447[[ 0.3324269 ]
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[[ 0.05308727 -0.15665007  0.06128528 ..., -0.14722669  0.18940024
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   0.18323035]]
Progress: 13.1% ... Training loss: 0.269 ... Validation loss: 0.428[[ 0.33928388]
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[[ 0.05290486 -0.15649473  0.06172256 ..., -0.14717354  0.18911105
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   0.18225849]]
Progress: 13.1% ... Training loss: 0.264 ... Validation loss: 0.432[[ 0.33901979]
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[[ 0.05289556 -0.15650784  0.06172787 ..., -0.14716658  0.18895453
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   0.18126695]]
Progress: 13.1% ... Training loss: 0.264 ... Validation loss: 0.432[[ 0.34308015]
 [-0.28978394]
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[[ 0.05386804 -0.1573796   0.05940584 ..., -0.14745186  0.19131183
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   0.18213127]]
Progress: 13.1% ... Training loss: 0.267 ... Validation loss: 0.438[[ 0.33570487]
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   0.18171487]]
Progress: 13.1% ... Training loss: 0.265 ... Validation loss: 0.431[[ 0.33475332]
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[[ 0.05310019 -0.15671671  0.06140384 ..., -0.14724145  0.18909156
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   0.18140265]]
Progress: 13.1% ... Training loss: 0.267 ... Validation loss: 0.432[[ 0.33511949]
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[[ 0.0531979  -0.15681034  0.0612421  ..., -0.14724138  0.18928466
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   0.18255067]]
Progress: 13.1% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.34005207]
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[[ 0.05381243 -0.15735189  0.05981819 ..., -0.14743933  0.191104
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   0.18270507]]
Progress: 13.1% ... Training loss: 0.264 ... Validation loss: 0.438[[ 0.33296597]
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[[ 0.05283885 -0.15653109  0.06208229 ..., -0.14716359  0.18880801
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   0.18234634]]
Progress: 13.1% ... Training loss: 0.272 ... Validation loss: 0.435[[ 0.3400909 ]
 [-0.2908611 ]
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[[ 0.05289147 -0.15657785  0.06209554 ..., -0.14718541  0.18907646
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   0.182207  ]]
Progress: 13.2% ... Training loss: 0.264 ... Validation loss: 0.438[[ 0.33823041]
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[[ 0.05228256 -0.15607723  0.06351713 ..., -0.14702272  0.18750799
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   0.18241221]]
Progress: 13.2% ... Training loss: 0.266 ... Validation loss: 0.438[[ 0.33885446]
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[[ 0.05179027 -0.15563769  0.06471365 ..., -0.14688001  0.18676709
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   0.18233115]]
Progress: 13.2% ... Training loss: 0.265 ... Validation loss: 0.437[[ 0.34001788]
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[[ 0.05183093 -0.15567191  0.06469816 ..., -0.14689129  0.18734356
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   0.18245889]]
Progress: 13.2% ... Training loss: 0.264 ... Validation loss: 0.438[[ 0.34497684]
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[[ 0.05303455 -0.15670753  0.06196911 ..., -0.14725897  0.19066624
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   0.18221364]]
Progress: 13.2% ... Training loss: 0.269 ... Validation loss: 0.445[[ 0.34098878]
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[[ 0.05352075 -0.15712227  0.06091367 ..., -0.14738524  0.19183924
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 [ 0.05691062 -0.02825957 -0.08319314 ...,  0.03820968  0.39294585
   0.18232482]]
Progress: 13.2% ... Training loss: 0.265 ... Validation loss: 0.437[[ 0.33985996]
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[[ 0.05310914 -0.15676775  0.0618964  ..., -0.14726593  0.19101639
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   0.18168396]]
Progress: 13.2% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.32719781]
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[[ 0.05223486 -0.15604892  0.06395906 ..., -0.14702626  0.18884643
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 [ 0.05707271 -0.02835254 -0.08345112 ...,  0.03816861  0.39343204
   0.18192611]]
Progress: 13.2% ... Training loss: 0.284 ... Validation loss: 0.443[[ 0.33862206]
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[[ 0.05296626 -0.15670763  0.06242656 ..., -0.14724652  0.19094797
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   0.18131219]]
Progress: 13.2% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.33463198]
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   0.18241816]]
Progress: 13.2% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.34542446]
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   0.18081223]]
Progress: 13.2% ... Training loss: 0.270 ... Validation loss: 0.447[[ 0.32704563]
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   0.18053604]]
Progress: 13.2% ... Training loss: 0.291 ... Validation loss: 0.449[[ 0.34846874]
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   0.17881807]]
Progress: 13.2% ... Training loss: 0.279 ... Validation loss: 0.459[[ 0.326777  ]
 [-0.29899263]
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 [ 0.05794324 -0.02908249 -0.08560325 ...,  0.03790616  0.39717818
   0.17940156]]
Progress: 13.2% ... Training loss: 0.293 ... Validation loss: 0.452[[ 0.34335746]
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   0.17955954]]
Progress: 13.2% ... Training loss: 0.267 ... Validation loss: 0.442[[ 0.33840401]
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[[ 0.05182948 -0.15597648  0.0646311  ..., -0.14709042  0.18900079
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   0.18015122]]
Progress: 13.3% ... Training loss: 0.264 ... Validation loss: 0.432[[ 0.3333686 ]
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 [ 0.05705158 -0.0282502  -0.0835564  ...,  0.03818156  0.39576899
   0.1814271 ]]
Progress: 13.3% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.33604683]
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[[ 0.05126661 -0.15544114  0.06623031 ..., -0.14691504  0.18785433
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 [ 0.05695902 -0.02812079 -0.08327295 ...,  0.0382223   0.39588     0.18169042]]
Progress: 13.3% ... Training loss: 0.264 ... Validation loss: 0.431[[ 0.33541572]
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[[ 0.0509186  -0.15511682  0.06697915 ..., -0.14680083  0.18685579
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   0.18054328]]
Progress: 13.3% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.33455509]
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[[ 0.05119594 -0.15532641  0.06636476 ..., -0.14687517  0.18776879
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   0.18072278]]
Progress: 13.3% ... Training loss: 0.264 ... Validation loss: 0.430[[ 0.33568277]
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[[ 0.05160976 -0.15570361  0.06558174 ..., -0.14700231  0.18881886
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 [ 0.05692337 -0.02802732 -0.08326744 ...,  0.03824077  0.3962429
   0.18160936]]
Progress: 13.3% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.3402483 ]
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[[ 0.05204085 -0.15604947  0.06469691 ..., -0.14713669  0.18986775
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  -0.24627982]
 [ 0.05667693 -0.0277948  -0.08280108 ...,  0.03831628  0.39573594
   0.18188914]]
Progress: 13.3% ... Training loss: 0.266 ... Validation loss: 0.437[[ 0.33936011]
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[[ 0.05180471 -0.1558167   0.06524521 ..., -0.14704798  0.18944786
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 [ 0.05655416 -0.02767258 -0.08260364 ...,  0.03835149  0.39560929
   0.18199611]]
Progress: 13.3% ... Training loss: 0.266 ... Validation loss: 0.433[[ 0.33028151]
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[[ 0.0511329  -0.15525556  0.06687226 ..., -0.14686893  0.18794613
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   0.18313937]]
Progress: 13.3% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.32362831]
 [-0.29792514]
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[[ 0.05005748 -0.15427032  0.06947659 ..., -0.14651947  0.18559854
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   0.18225091]]
Progress: 13.3% ... Training loss: 0.291 ... Validation loss: 0.456[[ 0.3470862 ]
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[[ 0.05219403 -0.15622072  0.06442304 ..., -0.1472364   0.1909989
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  -0.24635297]
 [ 0.05649126 -0.02761096 -0.08260332 ...,  0.03836489  0.39621165
   0.18177244]]
Progress: 13.3% ... Training loss: 0.289 ... Validation loss: 0.457[[ 0.32916906]
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[[ 0.05057556 -0.1548624   0.06808754 ..., -0.14680009  0.18704869
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  -0.24615218]
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   0.18286788]]
Progress: 13.3% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.33824623]
 [-0.28430306]
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[[ 0.05104458 -0.15528055  0.0669452  ..., -0.14694662  0.1885389
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  -0.2472373 ]
 [ 0.05589663 -0.02708526 -0.08125004 ...,  0.03853514  0.39550234
   0.18290567]]
Progress: 13.3% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.32998195]
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[[ 0.05054422 -0.15480718  0.06806035 ..., -0.1467967   0.18739804
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 [ 0.05576379 -0.02695639 -0.0810296  ...,  0.03857216  0.39546005
   0.18337335]]
Progress: 13.3% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.34109437]
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[[ 0.05154528 -0.15569498  0.06580844 ..., -0.14712274  0.18988657
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   0.18106675]]
Progress: 13.3% ... Training loss: 0.276 ... Validation loss: 0.437[[ 0.31790873]
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[[ 0.04980963 -0.15414102  0.06986294 ..., -0.14663146  0.18582002
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   0.18245094]]
Progress: 13.4% ... Training loss: 0.298 ... Validation loss: 0.465[[ 0.33872235]
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[[ 0.05101111 -0.15534211  0.06688122 ..., -0.14705922  0.18893027
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   0.18019244]]
Progress: 13.4% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.33689101]
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[[ 0.05147184 -0.1557581   0.06577234 ..., -0.14718569  0.19029989
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 [ 0.05683252 -0.02795957 -0.08384386 ...,  0.03821017  0.39921781
   0.18018254]]
Progress: 13.4% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.33140853]
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[[ 0.05109329 -0.15539567  0.0667043  ..., -0.14706512  0.18965466
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   0.18182311]]
Progress: 13.4% ... Training loss: 0.265 ... Validation loss: 0.428[[ 0.33385677]
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[[ 0.05127986 -0.15552782  0.06632485 ..., -0.14711911  0.19019026
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   0.18094261]]
Progress: 13.4% ... Training loss: 0.266 ... Validation loss: 0.427[[ 0.33098368]
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[[ 0.05070577 -0.15502477  0.06758766 ..., -0.14697539  0.18862543
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 [ 0.05670793 -0.02782793 -0.08367294 ...,  0.03824561  0.39970338
   0.17988995]]
Progress: 13.4% ... Training loss: 0.264 ... Validation loss: 0.431[[ 0.32630009]
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[[ 0.04994265 -0.15432715  0.0694498  ..., -0.14675036  0.18673462
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 [-0.18881483 -0.19373238 -0.13179916 ...,  0.10063705 -0.07756873
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 [ 0.05623003 -0.02737053 -0.08269591 ...,  0.03839334  0.39866808
   0.18080146]]
Progress: 13.4% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.34152346]
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[[ 0.05121603 -0.15551018  0.06652752 ..., -0.14715581  0.18985689
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 [ 0.05649113 -0.02759539 -0.08339547 ...,  0.03831963  0.3993873
   0.18015278]]
Progress: 13.4% ... Training loss: 0.278 ... Validation loss: 0.442[[ 0.33402754]
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[[ 0.0505126  -0.15495309  0.06804025 ..., -0.14697498  0.18810865
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   0.18187064]]
Progress: 13.4% ... Training loss: 0.263 ... Validation loss: 0.432[[ 0.32871517]
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[[ 0.05036691 -0.15481346  0.06845494 ..., -0.14692995  0.18773129
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   0.1829729 ]]
Progress: 13.4% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.32736898]
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 [ 1.55603571]
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[[ 0.0499712  -0.15443393  0.06942062 ..., -0.146802    0.1866787
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   0.18324679]]
Progress: 13.4% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.34291633]
 [-0.27777771]
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 [ 1.56629537]
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[[ 0.05094813 -0.1553284   0.06714388 ..., -0.1471211   0.18932146
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   0.1820906 ]]
Progress: 13.4% ... Training loss: 0.279 ... Validation loss: 0.452[[ 0.32830576]
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[[ 0.05009708 -0.15462739  0.06906353 ..., -0.14689406  0.18705786
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   0.18320281]]
Progress: 13.4% ... Training loss: 0.269 ... Validation loss: 0.439[[ 0.33922883]
 [-0.28132249]
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[[ 0.05059601 -0.15507228  0.06796249 ..., -0.14704921  0.18841744
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   0.18239648]]
Progress: 13.4% ... Training loss: 0.268 ... Validation loss: 0.442[[ 0.33468079]
 [-0.28615397]
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[[ 0.0506805  -0.15518595  0.06783145 ..., -0.14709237  0.18874223
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 [ 0.05529922 -0.02657839 -0.08099421 ...,  0.03863291  0.39752144
   0.18298155]]
Progress: 13.4% ... Training loss: 0.263 ... Validation loss: 0.433[[ 0.33763469]
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[[ 0.05091053 -0.15540896  0.06745537 ..., -0.14716177  0.18966708
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 [ 0.05497191 -0.02631534 -0.08024101 ...,  0.03871812  0.39698133
   0.18376262]]
Progress: 13.5% ... Training loss: 0.264 ... Validation loss: 0.435[[ 0.34397324]
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[[ 0.05178327 -0.15614186  0.06556281 ..., -0.14742652  0.19205963
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 [ 0.05555088 -0.02683117 -0.0814885  ...,  0.03854864  0.39851974
   0.18251246]]
Progress: 13.5% ... Training loss: 0.277 ... Validation loss: 0.447[[ 0.33466383]
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[[ 0.0511688  -0.15560873  0.06706283 ..., -0.14725679  0.19041138
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 [ 0.05554208 -0.02680066 -0.08149545 ...,  0.03855582  0.39868633
   0.18235533]]
Progress: 13.5% ... Training loss: 0.263 ... Validation loss: 0.434[[ 0.33252932]
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[[ 0.05077922 -0.15526503  0.06800835 ..., -0.14714534  0.18965843
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 [ 0.05556459 -0.02681325 -0.08154267 ...,  0.03855183  0.39892047
   0.18220393]]
Progress: 13.5% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.33356984]
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[[ 0.05060039 -0.15508954  0.06852021 ..., -0.1470963   0.18951735
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 [ 0.0552569  -0.0265267  -0.08086619 ...,  0.03864407  0.39846127
   0.18297957]]
Progress: 13.5% ... Training loss: 0.265 ... Validation loss: 0.436[[ 0.3334118 ]
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[[ 0.0504991  -0.15496784  0.0687386  ..., -0.14704967  0.18950078
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 [ 0.03988631  0.04698675  0.1064424  ..., -0.24494414 -0.02453918
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 [-0.18802806 -0.19449679 -0.13353061 ...,  0.10035733 -0.07617966
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 [ 0.05532815 -0.02655276 -0.08099595 ...,  0.03864059  0.3989818
   0.18286259]]
Progress: 13.5% ... Training loss: 0.265 ... Validation loss: 0.437[[ 0.34106353]
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[[ 0.05138769 -0.1557595   0.06669827 ..., -0.14731379  0.19173307
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 [-0.18811001 -0.194435   -0.13334708 ...,  0.10038688 -0.07646247
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   0.1818833 ]]
Progress: 13.5% ... Training loss: 0.269 ... Validation loss: 0.447[[ 0.32802282]
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[[ 0.0504954  -0.15497922  0.06861959 ..., -0.14705932  0.18954584
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 [ 0.0398964   0.04697675  0.10639359 ..., -0.24494818 -0.02449684
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   0.18308729]]
Progress: 13.5% ... Training loss: 0.271 ... Validation loss: 0.437[[ 0.33701655]
 [-0.28259503]
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[[ 0.05118549 -0.15551989  0.0671388  ..., -0.14724242  0.19115524
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   0.18244817]]
Progress: 13.5% ... Training loss: 0.267 ... Validation loss: 0.441[[ 0.33206209]
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[[ 0.05188358 -0.15612812  0.06548123 ..., -0.14743178  0.19302567
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 [ 0.05543964 -0.02663882 -0.08146527 ...,  0.03860057  0.40022216
   0.18217459]]
Progress: 13.5% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.3286813 ]
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  -0.24652222]
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   0.18376391]]
Progress: 13.5% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.34140971]
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[[ 0.05311782 -0.15731135  0.06256738 ..., -0.1478362   0.19636081
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   0.18264396]]
Progress: 13.5% ... Training loss: 0.272 ... Validation loss: 0.449[[ 0.34057357]
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[[ 0.05312511 -0.15733525  0.06264372 ..., -0.14784251  0.19641539
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   0.18099055]]
Progress: 13.5% ... Training loss: 0.269 ... Validation loss: 0.444[[ 0.32463302]
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[[ 0.0521678  -0.15648749  0.06486659 ..., -0.14756987  0.19416681
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   0.18156091]]
Progress: 13.5% ... Training loss: 0.276 ... Validation loss: 0.435[[ 0.33466916]
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   0.18151333]]
Progress: 13.5% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.33132456]
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[[ 0.05276905 -0.15704186  0.06357382 ..., -0.14780344  0.19580764
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   0.18140247]]
Progress: 13.6% ... Training loss: 0.264 ... Validation loss: 0.428[[ 0.3283101 ]
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[[ 0.05304093 -0.15727189  0.06303149 ..., -0.14789309  0.19635311
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 [ 0.05511578 -0.02623013 -0.08077516 ...,  0.03873211  0.40125098
   0.18246376]]
Progress: 13.6% ... Training loss: 0.266 ... Validation loss: 0.428[[ 0.33175917]
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[[ 0.05312003 -0.15733278  0.06295393 ..., -0.14792326  0.19681597
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 [ 0.0548486  -0.0259891  -0.08009586 ...,  0.0388189   0.40078477
   0.18309132]]
Progress: 13.6% ... Training loss: 0.263 ... Validation loss: 0.429[[ 0.3378491 ]
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[[ 0.05341488 -0.15758611  0.06233183 ..., -0.14801522  0.19738861
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   0.18289304]]
Progress: 13.6% ... Training loss: 0.267 ... Validation loss: 0.439[[ 0.32988248]
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[[ 0.05214231 -0.1564933   0.06517889 ..., -0.14767867  0.19453166
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  -0.246689  ]
 [ 0.0543381  -0.02551891 -0.07900552 ...,  0.03896585  0.40032562
   0.1845758 ]]
Progress: 13.6% ... Training loss: 0.265 ... Validation loss: 0.428[[ 0.33197126]
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[[ 0.05240988 -0.15673955  0.06458936 ..., -0.14776443  0.19512353
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 [-0.18813759 -0.19450658 -0.13328481 ...,  0.10031894 -0.07709164
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 [ 0.05431239 -0.02547899 -0.07902432 ...,  0.03898009  0.40029599
   0.18458393]]
Progress: 13.6% ... Training loss: 0.264 ... Validation loss: 0.428[[ 0.3303858 ]
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[[ 0.0522875  -0.15663327  0.06487501 ..., -0.14772178  0.19475529
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   0.18490644]]
Progress: 13.6% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.33208497]
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[[ 0.05242437 -0.15673503  0.06464929 ..., -0.14775524  0.19533657
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   0.18411978]]
Progress: 13.6% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.33948188]
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   0.18355361]]
Progress: 13.6% ... Training loss: 0.268 ... Validation loss: 0.441[[ 0.33320634]
 [-0.29259725]
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[[ 0.05257709 -0.15690053  0.0642533  ..., -0.14781445  0.19597976
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   0.18440887]]
Progress: 13.6% ... Training loss: 0.263 ... Validation loss: 0.429[[ 0.33864096]
 [-0.2877511 ]
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  -0.2456319 ]
 [ 0.05498132 -0.02603507 -0.08057482 ...,  0.03879681  0.40341355
   0.1826382 ]]
Progress: 13.6% ... Training loss: 0.269 ... Validation loss: 0.437[[ 0.34338209]
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[[ 0.05331981 -0.15756287  0.06261601 ..., -0.14802466  0.19837758
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   0.18311826]]
Progress: 13.6% ... Training loss: 0.278 ... Validation loss: 0.451[[ 0.32012674]
 [-0.30598643]
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[[ 0.05163213 -0.15615904  0.06634056 ..., -0.14758476  0.19433862
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   0.18494792]]
Progress: 13.6% ... Training loss: 0.303 ... Validation loss: 0.454[[ 0.34380259]
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[[ 0.05334269 -0.15782805  0.06233103 ..., -0.14819752  0.19871228
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   0.18343452]]
Progress: 13.6% ... Training loss: 0.277 ... Validation loss: 0.457[[ 0.32624822]
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   0.18459648]]
Progress: 13.6% ... Training loss: 0.280 ... Validation loss: 0.437[[ 0.33964751]
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[[ 0.05282796 -0.15746983  0.06333478 ..., -0.14810699  0.19781546
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   0.18403159]]
Progress: 13.7% ... Training loss: 0.269 ... Validation loss: 0.445[[ 0.33084985]
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[[ 0.05215329 -0.1569001   0.06482825 ..., -0.14792839  0.19634605
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 [ 0.05327383 -0.02462157 -0.07708385 ...,  0.03921507  0.4001722
   0.18650891]]
Progress: 13.7% ... Training loss: 0.266 ... Validation loss: 0.429[[ 0.34049779]
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[[ 0.05300802 -0.15771394  0.06289321 ..., -0.14817596  0.19829838
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   0.18720555]]
Progress: 13.7% ... Training loss: 0.270 ... Validation loss: 0.444[[ 0.32182596]
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[[ 0.05113678 -0.15609891  0.06717954 ..., -0.14766719  0.19384528
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   0.18818628]]
Progress: 13.7% ... Training loss: 0.289 ... Validation loss: 0.443[[ 0.33640984]
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[[ 0.05138265 -0.15635062  0.06668784 ..., -0.14775632  0.19425925
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   0.18747724]]
Progress: 13.7% ... Training loss: 0.264 ... Validation loss: 0.435[[ 0.33888451]
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[[ 0.05185871 -0.1567301   0.06574225 ..., -0.14788639  0.19541327
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   0.18652025]]
Progress: 13.7% ... Training loss: 0.269 ... Validation loss: 0.441[[ 0.32548614]
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[[ 0.05116974 -0.15616078  0.06742611 ..., -0.14770703  0.19367455
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 [-0.18824635 -0.19469254 -0.13313609 ...,  0.10021739 -0.07851016
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   0.18598052]]
Progress: 13.7% ... Training loss: 0.277 ... Validation loss: 0.436[[ 0.33844456]
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[[ 0.05197239 -0.15692219  0.06556115 ..., -0.1479587   0.19578452
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   0.18517936]]
Progress: 13.7% ... Training loss: 0.266 ... Validation loss: 0.441[[ 0.33103517]
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[[ 0.05125188 -0.15631861  0.06721897 ..., -0.14776861  0.19433862
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   0.18656576]]
Progress: 13.7% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.32414786]
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[[ 0.05041843 -0.1555306   0.06935186 ..., -0.1475118   0.19245585
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  -0.2466266 ]
 [ 0.05326216 -0.02457897 -0.07725603 ...,  0.03921544  0.40167054
   0.18646598]]
Progress: 13.7% ... Training loss: 0.281 ... Validation loss: 0.440[[ 0.34800039]
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[[ 0.05224761 -0.15722659  0.0651406  ..., -0.14809993  0.19700877
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  -0.24701491]
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   0.18506077]]
Progress: 13.7% ... Training loss: 0.299 ... Validation loss: 0.485[[ 0.32562621]
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[[ 0.05049464 -0.15578485  0.06897282 ..., -0.14767644  0.19298937
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   0.18561272]]
Progress: 13.7% ... Training loss: 0.276 ... Validation loss: 0.437[[ 0.33785075]
 [-0.28705647]
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[[ 0.05153504 -0.1567879   0.06668546 ..., -0.14800638  0.19532995
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   0.18426687]]
Progress: 13.7% ... Training loss: 0.266 ... Validation loss: 0.442[[ 0.32954832]
 [-0.29440113]
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[[ 0.05113007 -0.15647532  0.06770821 ..., -0.14789951  0.19445252
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   0.18469668]]
Progress: 13.7% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.3327206 ]
 [-0.29075519]
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[[ 0.05099359 -0.15632748  0.06808017 ..., -0.14784999  0.19408014
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 [ 0.05381514 -0.02512658 -0.07855173 ...,  0.03901734  0.404       0.18445632]]
Progress: 13.7% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.32601374]
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[[ 0.05009658 -0.15549968  0.07031689 ..., -0.14757064  0.19217206
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   0.18408438]]
Progress: 13.8% ... Training loss: 0.277 ... Validation loss: 0.439[[ 0.32827515]
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[[ 0.05046896 -0.15586281  0.06949573 ..., -0.14768687  0.19335857
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   0.18417004]]
Progress: 13.8% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.3408936 ]
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[[ 0.05124219 -0.15655767  0.06770107 ..., -0.14790969  0.19507885
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 [ 0.05382043 -0.02506265 -0.07866736 ...,  0.0390341   0.4047457
   0.18403974]]
Progress: 13.8% ... Training loss: 0.277 ... Validation loss: 0.459[[ 0.32833657]
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[[ 0.05041278 -0.15583929  0.06971433 ..., -0.14768895  0.19286727
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   0.18416188]]
Progress: 13.8% ... Training loss: 0.267 ... Validation loss: 0.436[[ 0.33017522]
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[[ 0.05049552 -0.15589829  0.06949096 ..., -0.14771048  0.19281963
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   0.18340398]]
Progress: 13.8% ... Training loss: 0.265 ... Validation loss: 0.437[[ 0.33678574]
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[[ 0.0514248  -0.15675037  0.06742943 ..., -0.14799763  0.19504845
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 [-0.18784682 -0.19518149 -0.1342446  ...,  0.09998872 -0.07784766
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 [ 0.05400457 -0.02518367 -0.07914594 ...,  0.0389878   0.40556391
   0.18341407]]
Progress: 13.8% ... Training loss: 0.268 ... Validation loss: 0.445[[ 0.33884971]
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[[ 0.05197113 -0.15725373  0.06615791 ..., -0.14814752  0.19636256
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 [-0.18822724 -0.19485812 -0.13342733 ...,  0.10009547 -0.07885167
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   0.18165401]]
Progress: 13.8% ... Training loss: 0.269 ... Validation loss: 0.447[[ 0.32901855]
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[[ 0.05126482 -0.15662691  0.06784261 ..., -0.14793379  0.19486584
  -0.1898618 ]
 [ 0.04021189  0.04661665  0.10489704 ..., -0.24508083 -0.02268457
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  -0.24852232]
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   0.18254507]]
Progress: 13.8% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.33527116]
 [-0.28701766]
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 [-0.77913273]
 [-0.20559068]
 [ 1.57058415]
 [ 0.38763562]
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[[ 0.05125156 -0.15660002  0.06788342 ..., -0.14792954  0.19484597
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  -0.24893528]
 [ 0.05447287 -0.0255505  -0.08027802 ...,  0.03887832  0.40727495
   0.18206427]]
Progress: 13.8% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.31990716]
 [-0.29949877]
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 [-0.79142197]
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 [ 1.55883957]
 [ 0.37470393]
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[[ 0.0494619  -0.15504865  0.07203355 ..., -0.14739617  0.19078848
  -0.18510952]
 [ 0.04020608  0.0466209   0.1048758  ..., -0.24508054 -0.02269178
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 [-0.18825524 -0.19485236 -0.133296   ...,  0.10009629 -0.07894568
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  -0.2476961 ]
 [ 0.05400845 -0.02513125 -0.07915425 ...,  0.03902802  0.40651121
   0.18335243]]
Progress: 13.8% ... Training loss: 0.298 ... Validation loss: 0.453[[ 0.33973528]
 [-0.28247695]
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 [ 1.57261425]
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[[ 0.04993996 -0.155507    0.07086341 ..., -0.14756712  0.19209005
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 [-0.18788968 -0.195193   -0.13418532 ...,  0.09996907 -0.07797054
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  -0.24885678]
 [ 0.05425683 -0.02535348 -0.07977719 ...,  0.03895093  0.40718204
   0.18266313]]
Progress: 13.8% ... Training loss: 0.269 ... Validation loss: 0.442[[ 0.32747117]
 [-0.29384154]
 [-0.78109738]
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 [ 1.56747786]
 [ 0.37999962]
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[[ 0.05015881 -0.15565037  0.07041953 ..., -0.14761926  0.19243476
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 [ 0.04038073  0.04648122  0.1044437  ..., -0.24512656 -0.02223496
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  -0.24904143]
 [ 0.05385728 -0.02499686 -0.07897087 ...,  0.03907105  0.40645942
   0.18336913]]
Progress: 13.8% ... Training loss: 0.269 ... Validation loss: 0.433[[ 0.33550537]
 [-0.28646864]
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 [ 1.57009008]
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[[ 0.05064843 -0.15613377  0.06929566 ..., -0.14780562  0.19375304
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 [-0.18810269 -0.19502708 -0.1338638  ...,  0.10001888 -0.07852839
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  -0.24995263]
 [ 0.0539917  -0.02511575 -0.07931375 ...,  0.03902787  0.40692956
   0.18304884]]
Progress: 13.8% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.3348907 ]
 [-0.28778221]
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 [ 1.57091159]
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[[ 0.05071692 -0.15618835  0.06914692 ..., -0.14782156  0.19382154
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 [-0.18791657 -0.19517699 -0.1343657  ...,  0.099967   -0.07820884
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  -0.24953203]
 [ 0.05391887 -0.02505422 -0.07923718 ...,  0.03905864  0.4069801
   0.1832404 ]]
Progress: 13.8% ... Training loss: 0.263 ... Validation loss: 0.433[[ 0.32632981]
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 [ 1.56464428]
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[[ 0.0501227  -0.15564643  0.07052773 ..., -0.14764188  0.19248011
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  -0.24988716]
 [ 0.05327709 -0.0244915  -0.07785692 ...,  0.03924491  0.40562868
   0.18466871]]
Progress: 13.8% ... Training loss: 0.273 ... Validation loss: 0.436[[ 0.33693186]
 [-0.28518846]
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 [ 1.57323817]
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[[ 0.05098511 -0.15644071  0.068505   ..., -0.14792134  0.19443342
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 [ 0.0398189   0.04697592  0.10574314 ..., -0.2449589  -0.0235616
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 [-0.18832012 -0.19485569 -0.13349    ...,  0.1000858  -0.07929351
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  -0.24994357]
 [ 0.0538819  -0.0250362  -0.07926735 ...,  0.03904979  0.40709876
   0.18305405]]
Progress: 13.9% ... Training loss: 0.266 ... Validation loss: 0.435[[ 0.3369531 ]
 [-0.28476473]
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[[ 0.05094234 -0.15638992  0.06864155 ..., -0.14790217  0.19413817
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  -0.24980279]
 [ 0.0541629  -0.02526382 -0.0799283  ...,  0.03898306  0.40786247
   0.1824587 ]]
Progress: 13.9% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.33013117]
 [-0.28944369]
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[[ 0.05038418 -0.15590228  0.07002512 ..., -0.14773968  0.1929683
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 [-0.1886631  -0.19458006 -0.13274401 ...,  0.10018278 -0.08032922
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  -0.2483968 ]
 [ 0.05454845 -0.02559311 -0.08078709 ...,  0.03887016  0.4089704
   0.18149898]]
Progress: 13.9% ... Training loss: 0.264 ... Validation loss: 0.430[[ 0.33557684]
 [-0.28453461]
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[[ 0.05086118 -0.15630645  0.06901799 ..., -0.14789245  0.19467811
  -0.18840191]
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 ..., 
 [-0.18864285 -0.19459185 -0.13283443 ...,  0.10017483 -0.08023794
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  -0.24825788]
 [ 0.0543816  -0.02543015 -0.08042767 ...,  0.03893312  0.40893495
   0.1819079 ]]
Progress: 13.9% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.3305992 ]
 [-0.2872673 ]
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[[ 0.05022872 -0.15567777  0.07049426 ..., -0.14765779  0.19365356
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 [ 0.03980853  0.04699327  0.10575349 ..., -0.24495783 -0.02348477
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 ..., 
 [-0.18839069 -0.19480867 -0.13335284 ...,  0.10010319 -0.07962992
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  -0.24789628]
 [ 0.05398301 -0.02504129 -0.07952924 ...,  0.03906373  0.40838001
   0.18279275]]
Progress: 13.9% ... Training loss: 0.263 ... Validation loss: 0.427[[ 0.33151812]
 [-0.28584967]
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[[ 0.05033657 -0.15581515  0.07037684 ..., -0.14769857  0.19402576
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 ..., 
 [-0.18828889 -0.19489695 -0.13355912 ...,  0.10007093 -0.07941029
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 [ 0.05409172 -0.02512812 -0.07978916 ...,  0.03902978  0.40884221
   0.18254907]]
Progress: 13.9% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.33715183]
 [-0.28021303]
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[[ 0.05081232 -0.15623845  0.06932997 ..., -0.1478386   0.1951623
  -0.1879593 ]
 [ 0.03985212  0.04695644  0.10557975 ..., -0.24496865 -0.02339413
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 [-0.18843344 -0.19476602 -0.13324334 ...,  0.10011449 -0.07983375
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   0.18105239]]
Progress: 13.9% ... Training loss: 0.268 ... Validation loss: 0.435[[ 0.33766643]
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[[ 0.05105173 -0.15646414  0.06898096 ..., -0.14791352  0.19555179
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   0.18077579]]
Progress: 13.9% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.32988957]
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   0.18103802]]
Progress: 13.9% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.33824234]
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[[ 0.05037281 -0.15589895  0.07061124 ..., -0.14772304  0.19368052
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   0.18074867]]
Progress: 13.9% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.331764  ]
 [-0.28420647]
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 [ 0.05483254 -0.02569665 -0.08162018 ...,  0.03883207  0.41137242
   0.18065215]]
Progress: 13.9% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.33127559]
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[[ 0.04973581 -0.15538272  0.07193323 ..., -0.14754734  0.19222834
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   0.18234838]]
Progress: 13.9% ... Training loss: 0.262 ... Validation loss: 0.427[[ 0.33834908]
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[[ 0.05038206 -0.15595845  0.07047476 ..., -0.14774076  0.19369809
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 [ 0.05448619 -0.02535529 -0.08083122 ...,  0.03896708  0.41115317
   0.18157567]]
Progress: 13.9% ... Training loss: 0.276 ... Validation loss: 0.436[[ 0.32370867]
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[[ 0.04964865 -0.15533251  0.07212305 ..., -0.14754142  0.19208394
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   0.18359528]]
Progress: 13.9% ... Training loss: 0.270 ... Validation loss: 0.433[[ 0.33024353]
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[[ 0.04961116 -0.15522147  0.07240137 ..., -0.14751758  0.19194448
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   0.18289976]]
Progress: 13.9% ... Training loss: 0.263 ... Validation loss: 0.425[[ 0.33544162]
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[[ 0.05000135 -0.15555724  0.07149117 ..., -0.1476382   0.19325792
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 [ 0.05386404 -0.02482692 -0.0793829  ...,  0.03913355  0.41057496
   0.18285411]]
Progress: 14.0% ... Training loss: 0.269 ... Validation loss: 0.429[[ 0.32872871]
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[[ 0.04957948 -0.15521745  0.07265476 ..., -0.14753672  0.19229829
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   0.18348376]]
Progress: 14.0% ... Training loss: 0.263 ... Validation loss: 0.427[[ 0.3358692 ]
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[[ 0.05008777 -0.15569167  0.07148115 ..., -0.14770814  0.19353443
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 [ 0.05351539 -0.02448681 -0.07859157 ...,  0.039258    0.41007474
   0.18360997]]
Progress: 14.0% ... Training loss: 0.270 ... Validation loss: 0.432[[ 0.32064598]
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[[ 0.04878421 -0.15459843  0.07451435 ..., -0.14734853  0.19032349
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 [ 0.05328855 -0.02429498 -0.07817166 ...,  0.03931343  0.40960927
   0.18396943]]
Progress: 14.0% ... Training loss: 0.281 ... Validation loss: 0.449[[ 0.34659157]
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[[ 0.05001929 -0.15574958  0.07162451 ..., -0.14777973  0.1931513
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 [ 0.05372694 -0.02470596 -0.07918328 ...,  0.03916529  0.41061396
   0.18299723]]
Progress: 14.0% ... Training loss: 0.296 ... Validation loss: 0.467[[ 0.3235948 ]
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[[ 0.04828993 -0.15438638  0.07537627 ..., -0.14734054  0.18913391
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   0.18451576]]
Progress: 14.0% ... Training loss: 0.279 ... Validation loss: 0.444[[ 0.34644054]
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[[ 0.05070072 -0.15663945  0.06970159 ..., -0.1481589   0.19516611
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   0.18440109]]
Progress: 14.0% ... Training loss: 0.292 ... Validation loss: 0.462[[ 0.33328532]
 [-0.28488774]
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 [ 1.57954309]
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[[ 0.04976093 -0.15584668  0.07182177 ..., -0.14791096  0.1932098
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   0.18495116]]
Progress: 14.0% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.33492537]
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   0.18437847]]
Progress: 14.0% ... Training loss: 0.264 ... Validation loss: 0.429[[ 0.32149244]
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[[ 0.0491168  -0.1553079   0.07350946 ..., -0.14774914  0.19149206
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   0.18535095]]
Progress: 14.0% ... Training loss: 0.287 ... Validation loss: 0.448[[ 0.33637723]
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[[ 0.04963986 -0.15578521  0.07236516 ..., -0.14791596  0.19277632
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   0.1835894 ]]
Progress: 14.0% ... Training loss: 0.265 ... Validation loss: 0.438[[ 0.33103799]
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[[ 0.04869387 -0.15498779  0.07460102 ..., -0.14764553  0.19036167
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   0.18386833]]
Progress: 14.0% ... Training loss: 0.265 ... Validation loss: 0.434[[ 0.33229396]
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[[ 0.04935731 -0.15556034  0.07317393 ..., -0.14784516  0.19213883
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   0.18437221]]
Progress: 14.0% ... Training loss: 0.263 ... Validation loss: 0.432[[ 0.32792947]
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[[ 0.04933796 -0.15553093  0.07326803 ..., -0.14782811  0.19213365
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   0.18539304]]
Progress: 14.0% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.34071044]
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[[ 0.05020674 -0.1563249   0.07119021 ..., -0.14809762  0.19424173
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 [ 0.05233133 -0.02348298 -0.07623742 ...,  0.03959391  0.40991177
   0.18605201]]
Progress: 14.0% ... Training loss: 0.278 ... Validation loss: 0.447[[ 0.3286401 ]
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[[ 0.04852937 -0.15498758  0.07484705 ..., -0.14768051  0.19005127
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 [ 0.05227902 -0.02344343 -0.07612521 ...,  0.03960662  0.40970006
   0.18615063]]
Progress: 14.1% ... Training loss: 0.267 ... Validation loss: 0.434[[ 0.33570725]
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[[ 0.04898341 -0.15544274  0.07385789 ..., -0.14783726  0.19110113
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 [ 0.05270702 -0.02381624 -0.07714871 ...,  0.03947811  0.41085792
   0.18504269]]
Progress: 14.1% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.33379581]
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[[ 0.04894121 -0.1553995   0.07390303 ..., -0.14781923  0.19084987
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 [-0.18827951 -0.19518884 -0.13396277 ...,  0.0998662  -0.07986345
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 [ 0.05285964 -0.02395362 -0.07746475 ...,  0.03944227  0.41122486
   0.18450327]]
Progress: 14.1% ... Training loss: 0.262 ... Validation loss: 0.433[[ 0.33093005]
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[[ 0.04894417 -0.15537996  0.0739273  ..., -0.14780134  0.19082353
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 [-0.18836023 -0.19510764 -0.13380205 ...,  0.09988431 -0.08008219
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 [ 0.05271972 -0.02381185 -0.07724231 ...,  0.03948912  0.41095926
   0.18466338]]
Progress: 14.1% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.33557915]
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[[ 0.04968528 -0.15603651  0.07206388 ..., -0.14802689  0.19261395
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 [ 0.05307741 -0.02410192 -0.0782575  ...,  0.03938448  0.41224596
   0.18342658]]
Progress: 14.1% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.33461374]
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[[ 0.04955598 -0.15594242  0.07256429 ..., -0.14798189  0.19225258
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 [-0.18811134 -0.1953153  -0.13425486 ...,  0.09981382 -0.07956411
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 [ 0.0526369  -0.02373141 -0.07735253 ...,  0.03951148  0.41143566
   0.18455294]]
Progress: 14.1% ... Training loss: 0.263 ... Validation loss: 0.433[[ 0.32786078]
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[[ 0.04876383 -0.15527216  0.0744596  ..., -0.14775293  0.19012049
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   0.18496419]]
Progress: 14.1% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.34131076]
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   0.18303273]]
Progress: 14.1% ... Training loss: 0.279 ... Validation loss: 0.451[[ 0.31532459]
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   0.18564735]]
Progress: 14.1% ... Training loss: 0.304 ... Validation loss: 0.466[[ 0.3292842 ]
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   0.18417356]]
Progress: 14.1% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.33065655]
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   0.18457325]]
Progress: 14.1% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.34099641]
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   0.18355429]]
Progress: 14.1% ... Training loss: 0.277 ... Validation loss: 0.450[[ 0.32933599]
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   0.18381628]]
Progress: 14.1% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32741646]
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   0.18391365]]
Progress: 14.1% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.32341392]
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[[ 0.04898135 -0.15569651  0.07362581 ..., -0.14800923  0.19094342
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   0.18427323]]
Progress: 14.1% ... Training loss: 0.266 ... Validation loss: 0.433[[ 0.33545195]
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[[ 0.04946574 -0.15613306  0.07251483 ..., -0.14816011  0.19234782
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   0.18371215]]
Progress: 14.2% ... Training loss: 0.270 ... Validation loss: 0.443[[ 0.31913221]
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[[ 0.04822728 -0.15509552  0.07542792 ..., -0.14783575  0.18920023
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   0.18341116]]
Progress: 14.2% ... Training loss: 0.284 ... Validation loss: 0.448[[ 0.33878879]
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[[ 0.0491739  -0.15597716  0.07313696 ..., -0.14815256  0.19148404
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   0.18194039]]
Progress: 14.2% ... Training loss: 0.277 ... Validation loss: 0.455[[ 0.33216102]
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[[ 0.04885962 -0.1556821   0.07389987 ..., -0.14805544  0.19050555
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   0.1815741 ]]
Progress: 14.2% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.32585678]
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[[ 0.04826611 -0.15511877  0.07525204 ..., -0.14787621  0.18959746
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   0.18008557]]
Progress: 14.2% ... Training loss: 0.264 ... Validation loss: 0.432[[ 0.33342521]
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   0.17859091]]
Progress: 14.2% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.33239561]
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   0.1790848 ]]
Progress: 14.2% ... Training loss: 0.265 ... Validation loss: 0.436[[ 0.32806474]
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 [ 0.05535681 -0.02599903 -0.08441983 ...,  0.03871633  0.42114244
   0.17721087]]
Progress: 14.2% ... Training loss: 0.263 ... Validation loss: 0.431[[ 0.31736774]
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   0.17791269]]
Progress: 14.2% ... Training loss: 0.279 ... Validation loss: 0.442[[ 0.33093511]
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[[ 0.05040154 -0.15695773  0.07066806 ..., -0.14849882  0.19507677
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   0.17687702]]
Progress: 14.2% ... Training loss: 0.264 ... Validation loss: 0.433[[ 0.33747349]
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   0.17582859]]
Progress: 14.2% ... Training loss: 0.281 ... Validation loss: 0.450[[ 0.32592611]
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   0.17673135]]
Progress: 14.2% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.31908935]
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[[ 0.04944913 -0.15613942  0.07312765 ..., -0.14822546  0.19313342
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   0.17784597]]
Progress: 14.2% ... Training loss: 0.273 ... Validation loss: 0.437[[ 0.32279627]
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   0.17866054]]
Progress: 14.2% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.332717  ]
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   0.17837533]]
Progress: 14.2% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.31903517]
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[[ 0.04867856 -0.15550237  0.07497581 ..., -0.14802256  0.19150858
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 [ 0.05423273 -0.02491731 -0.08193297 ...,  0.03910169  0.41964599
   0.17930215]]
Progress: 14.3% ... Training loss: 0.282 ... Validation loss: 0.443[[ 0.33316977]
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[[ 0.04935175 -0.15610122  0.07337887 ..., -0.14825693  0.19341261
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   0.17852837]]
Progress: 14.3% ... Training loss: 0.267 ... Validation loss: 0.441[[ 0.32251431]
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[[ 0.04838108 -0.15528475  0.07572818 ..., -0.14797982  0.19127226
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 [ 0.05422542 -0.02489284 -0.08190698 ...,  0.03909645  0.42015256
   0.17898023]]
Progress: 14.3% ... Training loss: 0.269 ... Validation loss: 0.435[[ 0.31921921]
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[[ 0.04753148 -0.15452223  0.07777216 ..., -0.14770499  0.18905483
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   0.17915359]]
Progress: 14.3% ... Training loss: 0.282 ... Validation loss: 0.443[[ 0.33437109]
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[[ 0.04820083 -0.15513693  0.07612187 ..., -0.14792976  0.19075985
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   0.17777696]]
Progress: 14.3% ... Training loss: 0.267 ... Validation loss: 0.442[[ 0.31802052]
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[[ 0.04715153 -0.15423264  0.07863871 ..., -0.14763029  0.18861522
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   0.17931274]]
Progress: 14.3% ... Training loss: 0.282 ... Validation loss: 0.445[[ 0.32773971]
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[[ 0.0481074  -0.15505287  0.07634824 ..., -0.14794263  0.1913047
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   0.17780146]]
Progress: 14.3% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.3145022 ]
 [-0.29219886]
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[[ 0.04714085 -0.15420785  0.07873817 ..., -0.14765793  0.18920801
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   0.17914769]]
Progress: 14.3% ... Training loss: 0.289 ... Validation loss: 0.451[[ 0.33626117]
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[[ 0.04872641 -0.15571764  0.0747463  ..., -0.14820987  0.19316912
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   0.17773109]]
Progress: 14.3% ... Training loss: 0.279 ... Validation loss: 0.449[[ 0.32574528]
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[[ 0.0472373  -0.15449784  0.07807911 ..., -0.14782217  0.18966143
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   0.17658082]]
Progress: 14.3% ... Training loss: 0.263 ... Validation loss: 0.429[[ 0.32848626]
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[[ 0.04741967 -0.15472582  0.07776102 ..., -0.14788112  0.18999368
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   0.17577977]]
Progress: 14.3% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32777237]
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[[ 0.04743121 -0.15474487  0.07790676 ..., -0.14787803  0.19000758
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   0.1763543 ]]
Progress: 14.3% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.32562187]
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[[ 0.04723303 -0.15456539  0.0783004  ..., -0.14782205  0.18951129
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   0.17750718]]
Progress: 14.3% ... Training loss: 0.263 ... Validation loss: 0.431[[ 0.33018361]
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[[ 0.04761843 -0.1549307   0.07750454 ..., -0.14794991  0.19071255
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   0.17652955]]
Progress: 14.3% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32615924]
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[[ 0.04774691 -0.1550342   0.07723272 ..., -0.14798142  0.19136055
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   0.17692968]]
Progress: 14.3% ... Training loss: 0.263 ... Validation loss: 0.429[[ 0.33138915]
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[[ 0.04800638 -0.1552635   0.07662869 ..., -0.14806118  0.19204353
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 [ 0.05485584 -0.02542955 -0.08394558 ...,  0.03888585  0.42431234
   0.17666081]]
Progress: 14.4% ... Training loss: 0.263 ... Validation loss: 0.429[[ 0.32301527]
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[[ 0.04800671 -0.15522299  0.07676051 ..., -0.14806497  0.19216868
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 [ 0.05469685 -0.02526956 -0.08375676 ...,  0.03894869  0.42421184
   0.17673833]]
Progress: 14.4% ... Training loss: 0.265 ... Validation loss: 0.430[[ 0.32577346]
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[[ 0.04797302 -0.1551716   0.07695716 ..., -0.14805689  0.1925471
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   0.17768972]]
Progress: 14.4% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.31535175]
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[[ 0.04712297 -0.15441836  0.07918825 ..., -0.14778927  0.19032248
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   0.17932606]]
Progress: 14.4% ... Training loss: 0.287 ... Validation loss: 0.450[[ 0.32968529]
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[[ 0.04746658 -0.15469913  0.07851449 ..., -0.14787851  0.19146925
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   0.17858287]]
Progress: 14.4% ... Training loss: 0.264 ... Validation loss: 0.435[[ 0.33054217]
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[[ 0.04807019 -0.15519224  0.07710717 ..., -0.1480586   0.19296366
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   0.17864384]]
Progress: 14.4% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.31678016]
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[[ 0.0468395  -0.15408835  0.07992507 ..., -0.14768549  0.18984737
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   0.17808155]]
Progress: 14.4% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.32603571]
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[[ 0.04720875 -0.15438649  0.07904134 ..., -0.14780273  0.19106272
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   0.17738657]]
Progress: 14.4% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.32828684]
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  -0.252464  ]
 [ 0.05414854 -0.02465964 -0.08257179 ...,  0.03914211  0.42483562
   0.17755175]]
Progress: 14.4% ... Training loss: 0.265 ... Validation loss: 0.432[[ 0.33218756]
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   0.17818349]]
Progress: 14.4% ... Training loss: 0.272 ... Validation loss: 0.437[[ 0.32776003]
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[[ 0.04801143 -0.15508562  0.07718237 ..., -0.14806195  0.19307816
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 [ 0.05351955 -0.02407665 -0.0814417  ...,  0.03933639  0.42406693
   0.17867767]]
Progress: 14.4% ... Training loss: 0.266 ... Validation loss: 0.428[[ 0.31513145]
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   0.17794021]]
Progress: 14.4% ... Training loss: 0.274 ... Validation loss: 0.439[[ 0.32413684]
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 [ 0.05436965 -0.02483988 -0.08350877 ...,  0.0390625   0.42666     0.17629995]]
Progress: 14.4% ... Training loss: 0.262 ... Validation loss: 0.426[[ 0.32510601]
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   0.17603413]]
Progress: 14.4% ... Training loss: 0.262 ... Validation loss: 0.427[[ 0.32363378]
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[[ 0.04744343 -0.15465468  0.07883378 ..., -0.14793561  0.19236285
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   0.17545226]]
Progress: 14.4% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.32811759]
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[[ 0.04740231 -0.15459354  0.07900437 ..., -0.14789858  0.19263751
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   0.17450869]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.32850214]
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[[ 0.04761326 -0.15475868  0.078549   ..., -0.14795978  0.19334247
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   0.17502662]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.432[[ 0.32337453]
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[[ 0.04726772 -0.15445332  0.07930571 ..., -0.14785013  0.19253046
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 [ 0.05480638 -0.02516672 -0.08460284 ...,  0.03895054  0.42894975
   0.17512271]]
Progress: 14.5% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.32617695]
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[[ 0.04739906 -0.15457567  0.0791152  ..., -0.14788108  0.19272414
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 [ 0.05523414 -0.02552321 -0.08555    ...,  0.03881812  0.43013971
   0.17400651]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.432[[ 0.32588856]
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[[ 0.04730444 -0.15452383  0.07934685 ..., -0.14786822  0.19301722
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   0.17460285]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32583779]
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   0.17494543]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.33251714]
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[[ 0.04772417 -0.15486916  0.07863824 ..., -0.1480088   0.19414506
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   0.17576928]]
Progress: 14.5% ... Training loss: 0.267 ... Validation loss: 0.438[[ 0.32348592]
 [-0.28079814]
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[[ 0.04764562 -0.15479751  0.07886489 ..., -0.1479953   0.19427864
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  -0.25191591]
 [ 0.05460853 -0.02494371 -0.0841169  ...,  0.0390209   0.42933901
   0.1754317 ]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.32585558]
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[[ 0.04749503 -0.1546833   0.0793772  ..., -0.14795862  0.19436255
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   0.17711054]]
Progress: 14.5% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.32135658]
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[[ 0.04669397 -0.1539979   0.08148358 ..., -0.14771485  0.19220663
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  -0.25087085]
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   0.17725427]]
Progress: 14.5% ... Training loss: 0.269 ... Validation loss: 0.434[[ 0.32712038]
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[[ 0.04712143 -0.15436393  0.08039973 ..., -0.14783458  0.19330589
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   0.17711162]]
Progress: 14.5% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.32072293]
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[[ 0.0464361  -0.15374174  0.08198758 ..., -0.1476057   0.1920718
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   0.17798531]]
Progress: 14.5% ... Training loss: 0.268 ... Validation loss: 0.432[[ 0.33544472]
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[[ 0.04737793 -0.15455546  0.07981699 ..., -0.14789831  0.19474707
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   0.17768355]]
Progress: 14.5% ... Training loss: 0.274 ... Validation loss: 0.445[[ 0.32056389]
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[[ 0.04631487 -0.15367029  0.08222255 ..., -0.14759965  0.1922008
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   0.17866747]]
Progress: 14.5% ... Training loss: 0.268 ... Validation loss: 0.431[[ 0.32967252]
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[[ 0.04635943 -0.15373154  0.08214027 ..., -0.14762987  0.19248512
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 [-0.18800498 -0.19604329 -0.13525488 ...,  0.0993904  -0.08100212
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   0.17861546]]
Progress: 14.5% ... Training loss: 0.263 ... Validation loss: 0.433[[ 0.32176155]
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[[ 0.04581757 -0.15322642  0.08361777 ..., -0.14746097  0.19160979
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 [ 0.05311596 -0.0234948  -0.08054466 ...,  0.03952718  0.42731099
   0.17919199]]
Progress: 14.6% ... Training loss: 0.264 ... Validation loss: 0.430[[ 0.32466038]
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[[ 0.04575555 -0.15318486  0.08374161 ..., -0.14744555  0.19133913
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 [ 0.05327878 -0.02361725 -0.08102457 ...,  0.0394803   0.42787431
   0.17854024]]
Progress: 14.6% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.32143868]
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[[ 0.04542674 -0.15290228  0.08455139 ..., -0.14735154  0.19077134
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 [ 0.05319629 -0.02354499 -0.08085418 ...,  0.03950784  0.42770986
   0.17868223]]
Progress: 14.6% ... Training loss: 0.266 ... Validation loss: 0.433[[ 0.33799767]
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[[ 0.04697753 -0.1542853   0.08098746 ..., -0.14784824  0.19483536
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 ..., 
 [-0.1875531  -0.19645181 -0.13620738 ...,  0.09925087 -0.07997726
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  -0.25070442]
 [ 0.05375021 -0.02406033 -0.0822149  ...,  0.03931263  0.42902118
   0.17708416]]
Progress: 14.6% ... Training loss: 0.284 ... Validation loss: 0.460[[ 0.32712501]
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[[ 0.04631436 -0.15377849  0.08249352 ..., -0.14768861  0.19333487
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 [ 0.05352874 -0.02386957 -0.0817749  ...,  0.03937615  0.42891869
   0.17762409]]
Progress: 14.6% ... Training loss: 0.261 ... Validation loss: 0.433[[ 0.3261478 ]
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   0.17710469]]
Progress: 14.6% ... Training loss: 0.262 ... Validation loss: 0.433[[ 0.33344713]
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[[ 0.04685237 -0.15420762  0.08154209 ..., -0.14783962  0.19499606
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   0.17614645]]
Progress: 14.6% ... Training loss: 0.271 ... Validation loss: 0.448[[ 0.32360143]
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[[ 0.04588883 -0.15338773  0.0837818  ..., -0.14758478  0.19261902
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  -0.24937579]
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   0.17595433]]
Progress: 14.6% ... Training loss: 0.263 ... Validation loss: 0.432[[ 0.32923632]
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[[ 0.04630197 -0.1537853   0.08286632 ..., -0.14770535  0.19373086
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  -0.249419  ]
 [ 0.0539119  -0.02412497 -0.08271012 ...,  0.03928307  0.43101395
   0.17630425]]
Progress: 14.6% ... Training loss: 0.265 ... Validation loss: 0.434[[ 0.31606158]
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   0.17748412]]
Progress: 14.6% ... Training loss: 0.278 ... Validation loss: 0.445[[ 0.33165922]
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   0.17656892]]
Progress: 14.6% ... Training loss: 0.266 ... Validation loss: 0.438[[ 0.32684641]
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[[ 0.04626874 -0.15383132  0.08305604 ..., -0.14774947  0.1938442
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 [ 0.05294002 -0.02329356 -0.08061997 ...,  0.03954963  0.4295901
   0.17857655]]
Progress: 14.6% ... Training loss: 0.261 ... Validation loss: 0.434[[ 0.32173884]
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 [ 0.05255742 -0.02293023 -0.07967959 ...,  0.03967211  0.42919778
   0.1794483 ]]
Progress: 14.6% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.32756588]
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[[ 0.04722784 -0.15458751  0.08097798 ..., -0.14802004  0.19649615
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 [ 0.05246037 -0.02283711 -0.07945012 ...,  0.03970289  0.42904804
   0.1796605 ]]
Progress: 14.6% ... Training loss: 0.263 ... Validation loss: 0.436[[ 0.31792429]
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[[ 0.0464931  -0.15393932  0.08255966 ..., -0.14780557  0.19478493
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 [ 0.0524275  -0.02278848 -0.07939421 ...,  0.03972081  0.42904618
   0.17974165]]
Progress: 14.6% ... Training loss: 0.268 ... Validation loss: 0.439[[ 0.31602442]
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[[ 0.04558948 -0.15310489  0.08474331 ..., -0.14751012  0.19249492
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 [ 0.05204877 -0.0224384  -0.07859891 ...,  0.03983589  0.42845268
   0.18026037]]
Progress: 14.7% ... Training loss: 0.272 ... Validation loss: 0.444[[ 0.32325449]
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[[ 0.04580478 -0.15330561  0.08434937 ..., -0.14758696  0.193345
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 [ 0.05215993 -0.02251579 -0.07886425 ...,  0.03980938  0.42914847
   0.17989951]]
Progress: 14.7% ... Training loss: 0.262 ... Validation loss: 0.436[[ 0.33192949]
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[[ 0.04671644 -0.15410048  0.08200773 ..., -0.14786416  0.19577415
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   0.17899986]]
Progress: 14.7% ... Training loss: 0.270 ... Validation loss: 0.445[[ 0.33575262]
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[[ 0.0475902  -0.15482758  0.08017167 ..., -0.14811177  0.19804578
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   0.17836037]]
Progress: 14.7% ... Training loss: 0.280 ... Validation loss: 0.456[[ 0.32102385]
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[[ 0.04674861 -0.15414039  0.0821012  ..., -0.14789324  0.195875
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   0.17793955]]
Progress: 14.7% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.33172133]
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[[ 0.04757927 -0.15486134  0.08004526 ..., -0.14814858  0.19816863
  -0.18180638]
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  -0.2493046 ]
 [ 0.05324297 -0.02341598 -0.08144523 ...,  0.03949849  0.43240041
   0.17710603]]
Progress: 14.7% ... Training loss: 0.267 ... Validation loss: 0.442[[ 0.3256366 ]
 [-0.27886986]
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[[ 0.04714161 -0.15447261  0.08107782 ..., -0.14802928  0.19717977
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   0.17701278]]
Progress: 14.7% ... Training loss: 0.261 ... Validation loss: 0.432[[ 0.32730559]
 [-0.27698673]
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[[ 0.04807012 -0.15532091  0.07884087 ..., -0.14829749  0.19959948
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  -0.24892181]
 [ 0.05330867 -0.02345143 -0.081614   ...,  0.03948608  0.43287645
   0.17664797]]
Progress: 14.7% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.32716093]
 [-0.27856686]
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[[ 0.04809392 -0.15537853  0.07885103 ..., -0.1483194   0.19962185
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  -0.24879482]
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   0.17646984]]
Progress: 14.7% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.32496853]
 [-0.28072962]
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[[ 0.04852473 -0.15574204  0.0778506  ..., -0.14845502  0.20078402
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  -0.24835389]
 [ 0.0535672  -0.02367729 -0.08237157 ...,  0.03941212  0.43392895
   0.17595903]]
Progress: 14.7% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.32598462]
 [-0.27908137]
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[[ 0.04879432 -0.15601408  0.07719809 ..., -0.14853926  0.20147483
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  -0.24702672]
 [ 0.05380113 -0.02387243 -0.0828853  ...,  0.03934109  0.43457881
   0.17530911]]
Progress: 14.7% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.32773194]
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[[ 0.04902491 -0.1562516   0.07683814 ..., -0.14861158  0.20218754
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 [ 0.05391752 -0.02398512 -0.08310309 ...,  0.039306    0.43511289
   0.17501071]]
Progress: 14.7% ... Training loss: 0.261 ... Validation loss: 0.434[[ 0.33095425]
 [-0.27551272]
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[[ 0.04921699 -0.1564118   0.07634567 ..., -0.14868008  0.20273563
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 [ 0.05408878 -0.02412557 -0.08354577 ...,  0.03924994  0.43561914
   0.17446759]]
Progress: 14.7% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.33335136]
 [-0.27559566]
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[[ 0.05006342 -0.15712029  0.07455305 ..., -0.14894694  0.20487037
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 [-0.18754369 -0.19656012 -0.1361223  ...,  0.09918881 -0.08138064
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 [ 0.05417356 -0.02418069 -0.08366836 ...,  0.03923426  0.43605665
   0.17430223]]
Progress: 14.7% ... Training loss: 0.265 ... Validation loss: 0.439[[ 0.32090026]
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[[ 0.04907835 -0.15631295  0.07684287 ..., -0.14866484  0.20242593
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  -0.24636404]
 [ 0.05345625 -0.02354619 -0.08219667 ...,  0.03947015  0.43458898
   0.17570883]]
Progress: 14.7% ... Training loss: 0.270 ... Validation loss: 0.435[[ 0.32544621]
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[[ 0.04904571 -0.15625032  0.07699888 ..., -0.14864063  0.20256067
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  -0.24631662]
 [ 0.05337308 -0.02345946 -0.08202522 ...,  0.03949795  0.43463283
   0.17608572]]
Progress: 14.8% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.33847175]
 [-0.27037136]
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[[ 0.04980455 -0.15692858  0.07526138 ..., -0.14890092  0.20413766
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 [ 0.05407721 -0.02407632 -0.08366618 ...,  0.03927062  0.4364925
   0.17434882]]
Progress: 14.8% ... Training loss: 0.279 ... Validation loss: 0.450[[ 0.31975823]
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[[ 0.048117   -0.15554445  0.07920429 ..., -0.14842269  0.19990734
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   0.603391  ]
 ..., 
 [-0.18768516 -0.19650774 -0.13580814 ...,  0.09920605 -0.08200011
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  -0.24530816]
 [ 0.05407451 -0.02407952 -0.08364598 ...,  0.03927087  0.43659713
   0.17433735]]
Progress: 14.8% ... Training loss: 0.278 ... Validation loss: 0.444[[ 0.33818946]
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[[ 0.04965926 -0.15694502  0.07546946 ..., -0.14896346  0.20396344
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 [-0.18720379 -0.19694761 -0.136959   ...,  0.09903709 -0.08080224
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 [ 0.05396017 -0.02395964 -0.08338019 ...,  0.03931869  0.43639969
   0.17468042]]
Progress: 14.8% ... Training loss: 0.277 ... Validation loss: 0.452[[ 0.32059444]
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[[ 0.04884256 -0.15628775  0.07733104 ..., -0.14873857  0.20197999
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   0.17647792]]
Progress: 14.8% ... Training loss: 0.271 ... Validation loss: 0.436[[ 0.33502226]
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 [ 0.05344213 -0.02350653 -0.08228158 ...,  0.03946249  0.43587396
   0.17597177]]
Progress: 14.8% ... Training loss: 0.268 ... Validation loss: 0.439[[ 0.33873533]
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[[ 0.05072887 -0.15783881  0.07306053 ..., -0.14929693  0.20716342
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   0.17683885]]
Progress: 14.8% ... Training loss: 0.283 ... Validation loss: 0.453[[ 0.32233166]
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[[ 0.04933882 -0.15674089  0.07625924 ..., -0.14893507  0.20351619
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 [ 0.05283287 -0.02298701 -0.08092737 ...,  0.0396425   0.43475437
   0.17751551]]
Progress: 14.8% ... Training loss: 0.267 ... Validation loss: 0.432[[ 0.33342414]
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[[ 0.05037953 -0.15767305  0.07392033 ..., -0.14927079  0.20610645
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  -0.24529452]
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   0.17709001]]
Progress: 14.8% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.32493728]
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[[ 0.04940404 -0.15690288  0.07612843 ..., -0.14899441  0.20359991
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   0.17763722]]
Progress: 14.8% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.32692386]
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   0.17775528]]
Progress: 14.8% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32406338]
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   0.17667512]]
Progress: 14.8% ... Training loss: 0.267 ... Validation loss: 0.437[[ 0.33380136]
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 [ 0.05318082 -0.02326194 -0.0818544  ...,  0.03953888  0.43612734
   0.17625637]]
Progress: 14.8% ... Training loss: 0.264 ... Validation loss: 0.434[[ 0.33010554]
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[[ 0.04938643 -0.1568804   0.07646277 ..., -0.14900368  0.20336306
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 [ 0.05323548 -0.0232952  -0.08190103 ...,  0.03952779  0.43628374
   0.17611726]]
Progress: 14.8% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.333254  ]
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[[ 0.04903093 -0.15657146  0.07748393 ..., -0.148891    0.20251432
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 [ 0.05356359 -0.02357274 -0.08263342 ...,  0.03943099  0.437151    0.1753348 ]]
Progress: 14.8% ... Training loss: 0.262 ... Validation loss: 0.433[[ 0.32776149]
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[[ 0.04906745 -0.15656982  0.07756799 ..., -0.1488941   0.20263568
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 [ 0.05408721 -0.02398524 -0.08382104 ...,  0.03928584  0.43866682
   0.17417036]]
Progress: 14.9% ... Training loss: 0.261 ... Validation loss: 0.429[[ 0.33213289]
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[[ 0.04957245 -0.15695543  0.07648061 ..., -0.14904595  0.20395573
  -0.1866994 ]
 [ 0.04046364  0.04629512  0.10306411 ..., -0.24531715 -0.01805507
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 [ 0.05421523 -0.02408788 -0.08415287 ...,  0.0392518   0.43915672
   0.17384616]]
Progress: 14.9% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.32625597]
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[[ 0.04888171 -0.15635195  0.07811759 ..., -0.14885165  0.20238647
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 [ 0.05384863 -0.02376858 -0.08331254 ...,  0.03936333  0.43844967
   0.1748174 ]]
Progress: 14.9% ... Training loss: 0.261 ... Validation loss: 0.428[[ 0.31990258]
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[[ 0.04824304 -0.15583063  0.07973887 ..., -0.14866591  0.20072551
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 [ 0.05416394 -0.02402524 -0.08405065 ...,  0.03926892  0.43947275
   0.17400997]]
Progress: 14.9% ... Training loss: 0.274 ... Validation loss: 0.443[[ 0.33925045]
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[[ 0.04985114 -0.15724924  0.07597224 ..., -0.14919243  0.2049612
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   0.17267658]]
Progress: 14.9% ... Training loss: 0.281 ... Validation loss: 0.450[[ 0.31790848]
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   0.17476695]]
Progress: 14.9% ... Training loss: 0.275 ... Validation loss: 0.439[[ 0.33091929]
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[[ 0.05031039 -0.15765459  0.07489868 ..., -0.14936916  0.20626279
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 [ 0.05344421 -0.02341358 -0.08247191 ...,  0.03946446  0.43854236
   0.17577827]]
Progress: 14.9% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32996028]
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  -0.2456283 ]
 [ 0.05366706 -0.02357858 -0.08295843 ...,  0.03940683  0.43908777
   0.17509069]]
Progress: 14.9% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.33076085]
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   0.17479499]]
Progress: 14.9% ... Training loss: 0.263 ... Validation loss: 0.433[[ 0.32522056]
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[[ 0.05138911 -0.1585084   0.07228534 ..., -0.14965276  0.20861393
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   0.1748657 ]]
Progress: 14.9% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.32494777]
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   0.1755278 ]]
Progress: 14.9% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.3244833 ]
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[[ 0.05097485 -0.15809153  0.0733885  ..., -0.14951111  0.20814892
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 [ 0.0537884  -0.0236387  -0.08337347 ...,  0.03938411  0.44042695
   0.17480551]]
Progress: 14.9% ... Training loss: 0.262 ... Validation loss: 0.427[[ 0.32702557]
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   0.17352747]]
Progress: 14.9% ... Training loss: 0.262 ... Validation loss: 0.426[[ 0.33327654]
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[[ 0.05140303 -0.15842407  0.07234071 ..., -0.14964195  0.20943264
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 [ 0.05462626 -0.02438406 -0.08540045 ...,  0.0391327   0.44280055
   0.1727364 ]]
Progress: 14.9% ... Training loss: 0.268 ... Validation loss: 0.434[[ 0.32563277]
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[[ 0.0507085  -0.157828    0.07413338 ..., -0.14944055  0.20749952
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   0.17361323]]
Progress: 14.9% ... Training loss: 0.262 ... Validation loss: 0.425[[ 0.34159114]
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[[ 0.05165537 -0.15866039  0.07192862 ..., -0.14973879  0.20973315
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   0.17320348]]
Progress: 15.0% ... Training loss: 0.296 ... Validation loss: 0.464[[ 0.32728811]
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[[ 0.05126284 -0.15833187  0.0726224  ..., -0.14962558  0.20886108
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 [ 0.0536518  -0.02354804 -0.08329866 ...,  0.0393968   0.44119008
   0.17488093]]
Progress: 15.0% ... Training loss: 0.262 ... Validation loss: 0.422[[ 0.33122779]
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[[ 0.05176174 -0.15874308  0.07149485 ..., -0.14977728  0.2104668
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   0.17490792]]
Progress: 15.0% ... Training loss: 0.268 ... Validation loss: 0.424[[ 0.32547447]
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[[ 0.05191719 -0.15887586  0.07111032 ..., -0.14982217  0.21087765
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   0.17423998]]
Progress: 15.0% ... Training loss: 0.263 ... Validation loss: 0.423[[ 0.32409225]
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[[ 0.05132975 -0.1583612   0.07263368 ..., -0.14964738  0.20942352
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   0.17521336]]
Progress: 15.0% ... Training loss: 0.263 ... Validation loss: 0.425[[ 0.33218915]
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[[ 0.0519027  -0.15886087  0.07138846 ..., -0.14982492  0.21110492
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   0.17618144]]
Progress: 15.0% ... Training loss: 0.268 ... Validation loss: 0.428[[ 0.33191836]
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[[ 0.0522972  -0.15916661  0.07057991 ..., -0.14993162  0.21189373
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  -0.24451643]
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   0.17611666]]
Progress: 15.0% ... Training loss: 0.267 ... Validation loss: 0.429[[ 0.32130523]
 [-0.28611577]
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[[ 0.05107892 -0.15809735  0.07360465 ..., -0.1495805   0.20919487
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  -0.24419384]
 [ 0.0527466  -0.02264447 -0.0812303  ...,  0.03971653  0.44069302
   0.17657357]]
Progress: 15.0% ... Training loss: 0.265 ... Validation loss: 0.426[[ 0.3236541 ]
 [-0.28329461]
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  -0.24421704]
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   0.17726262]]
Progress: 15.0% ... Training loss: 0.262 ... Validation loss: 0.425[[ 0.32856807]
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[[ 0.05144284 -0.15839729  0.07294266 ..., -0.14968444  0.20981579
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   0.17772047]]
Progress: 15.0% ... Training loss: 0.262 ... Validation loss: 0.426[[ 0.32199855]
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[[ 0.05020325 -0.1573365   0.07598666 ..., -0.14931957  0.20706878
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   0.17900332]]
Progress: 15.0% ... Training loss: 0.264 ... Validation loss: 0.428[[ 0.33048513]
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[[ 0.05119823 -0.15820991  0.07365313 ..., -0.14963879  0.20969044
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   0.17800659]]
Progress: 15.0% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.32424048]
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[[ 0.0507919  -0.15790105  0.07469339 ..., -0.1495156   0.20879635
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 [ 0.0510134  -0.02105988 -0.07733765 ...,  0.04027049  0.43789813
   0.18047335]]
Progress: 15.0% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.32469546]
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[[ 0.05047286 -0.15758721  0.0757799  ..., -0.14939731  0.20817405
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 [ 0.05153501 -0.0215026  -0.07853163 ...,  0.04011944  0.43952725
   0.17939025]]
Progress: 15.0% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.33007708]
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[[ 0.05079475 -0.15781588  0.075076   ..., -0.14948842  0.20895958
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 [ 0.0521221  -0.02200237 -0.07992638 ...,  0.0399438   0.44116032
   0.17786804]]
Progress: 15.0% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.33346843]
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[[ 0.05107384 -0.15804862  0.0744591  ..., -0.14958367  0.20978845
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   0.17732994]]
Progress: 15.1% ... Training loss: 0.274 ... Validation loss: 0.438[[ 0.32556442]
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[[ 0.05057776 -0.15758114  0.07569833 ..., -0.149434    0.20837775
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 [-0.18686845 -0.19750346 -0.13801315 ...,  0.09873602 -0.08189222
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  -0.24532704]
 [ 0.05240837 -0.02221786 -0.08061178 ...,  0.03986561  0.4422051
   0.17728629]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.425[[ 0.32517882]
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[[ 0.05063522 -0.15762661  0.07556039 ..., -0.14944938  0.20837548
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   0.17699621]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.425[[ 0.32537283]
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[[ 0.0507783  -0.15773213  0.07535648 ..., -0.14946329  0.20856254
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   0.17653343]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.32286757]
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[[ 0.05097784 -0.15792039  0.07510186 ..., -0.1495348   0.20927814
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 [ 0.05235336 -0.0221321  -0.08061465 ...,  0.03989444  0.4425632
   0.17712367]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.422[[ 0.32446355]
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[[ 0.05076574 -0.15771525  0.07582209 ..., -0.14946108  0.20882578
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   0.17659307]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.424[[ 0.32594794]
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[[ 0.05060777 -0.15760207  0.07627354 ..., -0.14940991  0.20878715
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   0.17628189]]
Progress: 15.1% ... Training loss: 0.262 ... Validation loss: 0.424[[ 0.32054233]
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   0.17749783]]
Progress: 15.1% ... Training loss: 0.262 ... Validation loss: 0.425[[ 0.32105159]
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[[ 0.04975562 -0.15678423  0.07845142 ..., -0.14912801  0.20666606
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   0.17638185]]
Progress: 15.1% ... Training loss: 0.261 ... Validation loss: 0.423[[ 0.32775215]
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   0.17561156]]
Progress: 15.1% ... Training loss: 0.267 ... Validation loss: 0.430[[ 0.3149868 ]
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   0.17654242]]
Progress: 15.1% ... Training loss: 0.272 ... Validation loss: 0.434[[ 0.31879399]
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   0.17611673]]
Progress: 15.1% ... Training loss: 0.264 ... Validation loss: 0.427[[ 0.32785231]
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   0.17537533]]
Progress: 15.1% ... Training loss: 0.265 ... Validation loss: 0.428[[ 0.31508127]
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[[ 0.04744359 -0.1546759   0.08432852 ..., -0.14841944  0.20231324
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 [ 0.05204272 -0.02177924 -0.07996122 ...,  0.03998195  0.4441691
   0.17728983]]
Progress: 15.1% ... Training loss: 0.268 ... Validation loss: 0.429[[ 0.32454916]
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[[ 0.04722343 -0.15447952  0.08494356 ..., -0.14835407  0.20182334
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   0.1769644 ]]
Progress: 15.1% ... Training loss: 0.260 ... Validation loss: 0.424[[ 0.32964264]
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[[ 0.04786003 -0.15503358  0.08330105 ..., -0.14855168  0.2033727
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   0.17619524]]
Progress: 15.2% ... Training loss: 0.266 ... Validation loss: 0.430[[ 0.3275491 ]
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[[ 0.04810856 -0.1552389   0.08285855 ..., -0.14862554  0.20414251
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 ..., 
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   0.17493042]]
Progress: 15.2% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.32917503]
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[[ 0.04814289 -0.15523563  0.08286584 ..., -0.14861811  0.20409203
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   0.17536829]]
Progress: 15.2% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.32049721]
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[[ 0.04705495 -0.15431238  0.08552547 ..., -0.14830689  0.20127386
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   0.17570179]]
Progress: 15.2% ... Training loss: 0.264 ... Validation loss: 0.429[[ 0.33153683]
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   0.17505789]]
Progress: 15.2% ... Training loss: 0.267 ... Validation loss: 0.432[[ 0.32251355]
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[[ 0.04750305 -0.1547206   0.08434836 ..., -0.14846761  0.20254594
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   0.17506924]]
Progress: 15.2% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.32449142]
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   0.17558966]]
Progress: 15.2% ... Training loss: 0.260 ... Validation loss: 0.424[[ 0.32658894]
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   0.17483634]]
Progress: 15.2% ... Training loss: 0.264 ... Validation loss: 0.426[[ 0.31614369]
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[[ 0.04765941 -0.15477935  0.08410098 ..., -0.14852311  0.20354793
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   0.17707906]]
Progress: 15.2% ... Training loss: 0.265 ... Validation loss: 0.428[[ 0.31883571]
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   0.17739716]]
Progress: 15.2% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.32510898]
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   0.17650093]]
Progress: 15.2% ... Training loss: 0.261 ... Validation loss: 0.428[[ 0.3236058 ]
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   0.17622203]]
Progress: 15.2% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.31495501]
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[[ 0.04781087 -0.1549033   0.08411581 ..., -0.14855419  0.20400557
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 [ 0.05268597 -0.02211359 -0.0816286  ...,  0.03983087  0.44877268
   0.17540986]]
Progress: 15.2% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.32351843]
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[[ 0.04772084 -0.15480707  0.08435842 ..., -0.14851423  0.20413693
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   0.17423699]]
Progress: 15.2% ... Training loss: 0.260 ... Validation loss: 0.428[[ 0.32814592]
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[[ 0.04791416 -0.15497801  0.08395824 ..., -0.14857168  0.20484514
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   0.17478324]]
Progress: 15.2% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.31971184]
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[[ 0.04705659 -0.15425701  0.08589058 ..., -0.14832368  0.20252496
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 [ 0.05276242 -0.02218731 -0.08205338 ...,  0.03980015  0.44936437
   0.17511021]]
Progress: 15.3% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.32326199]
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[[ 0.0475201  -0.15467253  0.0847979  ..., -0.1484795   0.20378888
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 [ 0.05253647 -0.02198016 -0.0814791  ...,  0.03986932  0.44920291
   0.17561396]]
Progress: 15.3% ... Training loss: 0.259 ... Validation loss: 0.426[[ 0.32369698]
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[[ 0.04746179 -0.15461484  0.08524481 ..., -0.14846606  0.20332368
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   0.17524509]]
Progress: 15.3% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32205199]
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   0.1749306 ]]
Progress: 15.3% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32507135]
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[[ 0.04726454 -0.15442851  0.0858542  ..., -0.14839527  0.20295463
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   0.17456094]]
Progress: 15.3% ... Training loss: 0.260 ... Validation loss: 0.430[[ 0.32791969]
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   0.17478783]]
Progress: 15.3% ... Training loss: 0.265 ... Validation loss: 0.430[[ 0.31520465]
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[[ 0.0466473  -0.15380837  0.08764706 ..., -0.14819392  0.20224456
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   0.17644447]]
Progress: 15.3% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.326646  ]
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   0.17449503]]
Progress: 15.3% ... Training loss: 0.263 ... Validation loss: 0.430[[ 0.32758201]
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[[ 0.04814667 -0.15513458  0.0841819  ..., -0.14866012  0.20562742
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 [ 0.05287651 -0.02218142 -0.08250794 ...,  0.03978799  0.45234318
   0.17394835]]
Progress: 15.3% ... Training loss: 0.265 ... Validation loss: 0.430[[ 0.31926006]
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 [ 0.05260574 -0.02191548 -0.08192252 ...,  0.03987401  0.45212847
   0.17448331]]
Progress: 15.3% ... Training loss: 0.260 ... Validation loss: 0.426[[ 0.32253952]
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[[ 0.04782901 -0.15480298  0.08499308 ..., -0.14857717  0.20533249
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   0.17504443]]
Progress: 15.3% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.32253678]
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   0.17524754]]
Progress: 15.3% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.31240847]
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[[ 0.04730149 -0.15427679  0.0862025  ..., -0.14839878  0.20437636
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 [ 0.05138234 -0.02074793 -0.07896996 ...,  0.04027285  0.45007972
   0.17760848]]
Progress: 15.3% ... Training loss: 0.270 ... Validation loss: 0.434[[ 0.31198776]
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[[ 0.04698322 -0.15397946  0.08701667 ..., -0.14830183  0.20356835
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   0.17753863]]
Progress: 15.3% ... Training loss: 0.271 ... Validation loss: 0.438[[ 0.32296354]
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[[ 0.04741593 -0.1544037   0.08598204 ..., -0.1484547   0.20459127
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   0.17714894]]
Progress: 15.3% ... Training loss: 0.260 ... Validation loss: 0.428[[ 0.32907907]
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[[ 0.04830653 -0.1551614   0.08381179 ..., -0.14870311  0.20658024
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  -0.24614155]
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   0.17625074]]
Progress: 15.4% ... Training loss: 0.273 ... Validation loss: 0.438[[ 0.31174298]
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[[ 0.04729301 -0.15425838  0.08617612 ..., -0.14840722  0.20443356
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 [ 0.05130083 -0.02062918 -0.0790067  ...,  0.04030686  0.45084653
   0.17747981]]
Progress: 15.4% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.3212829 ]
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[[ 0.04794818 -0.15492234  0.08459222 ..., -0.14864385  0.20597937
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   0.17621739]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.426[[ 0.32244557]
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[[ 0.04805766 -0.15499487  0.08434983 ..., -0.14865781  0.20636679
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   0.17627004]]
Progress: 15.4% ... Training loss: 0.261 ... Validation loss: 0.425[[ 0.32343924]
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[[ 0.04804096 -0.15498766  0.08427452 ..., -0.14866461  0.20644746
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  -0.24425165]
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   0.17643983]]
Progress: 15.4% ... Training loss: 0.262 ... Validation loss: 0.427[[ 0.31014971]
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 [ 1.59386333]
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[[ 0.04756566 -0.15454196  0.08554527 ..., -0.14852733  0.20517783
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  -0.24420559]
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   0.17699326]]
Progress: 15.4% ... Training loss: 0.278 ... Validation loss: 0.447[[ 0.3215752 ]
 [-0.28117512]
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  -0.2452613 ]
 [ 0.0509347  -0.02021997 -0.07817976 ...,  0.04047132  0.45129576
   0.17837653]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.426[[ 0.32248037]
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 [ 0.0508602  -0.02013708 -0.07818718 ...,  0.04049514  0.45158306
   0.17825962]]
Progress: 15.4% ... Training loss: 0.262 ... Validation loss: 0.427[[ 0.31836057]
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[[ 0.04861691 -0.15549803  0.08330523 ..., -0.14883149  0.2076514
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 [ 0.05064438 -0.01992092 -0.07768111 ...,  0.04057129  0.45124651
   0.17874935]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.32699752]
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[[ 0.04867373 -0.15555375  0.08314463 ..., -0.14886129  0.20811081
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 [ 0.05133023 -0.02053063 -0.07937093 ...,  0.04035498  0.45318494
   0.17703703]]
Progress: 15.4% ... Training loss: 0.266 ... Validation loss: 0.435[[ 0.31561413]
 [-0.28689708]
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[[ 0.04767889 -0.15469809  0.08570582 ..., -0.1485898   0.20617581
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 [ 0.0509944  -0.02022742 -0.07842336 ...,  0.04045045  0.45284759
   0.17809992]]
Progress: 15.4% ... Training loss: 0.263 ... Validation loss: 0.432[[ 0.32019265]
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[[ 0.04734035 -0.15438373  0.08670579 ..., -0.14848383  0.20524828
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  -0.24495756]
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   0.17873523]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.32002488]
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[[ 0.0476347  -0.15467433  0.08586072 ..., -0.14857649  0.20593072
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 [ 0.05082646 -0.02004258 -0.07815317 ...,  0.0405146   0.45284762
   0.17836272]]
Progress: 15.4% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32367842]
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[[ 0.04816632 -0.15515441  0.08468082 ..., -0.14873973  0.20759609
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 [-0.18617102 -0.198329   -0.1395296  ...,  0.09840437 -0.08209495
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  -0.24516171]
 [ 0.05072225 -0.0199583  -0.07793969 ...,  0.04053816  0.45272458
   0.17872977]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.32472544]
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[[ 0.04846179 -0.15540534  0.08421372 ..., -0.14882704  0.20837117
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 [-0.18575223 -0.19868811 -0.14055469 ...,  0.09828885 -0.08120039
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  -0.24475794]
 [ 0.05034142 -0.01960529 -0.07700362 ...,  0.04065913  0.45208695
   0.17968741]]
Progress: 15.4% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.31730111]
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[[ 0.04814684 -0.15509321  0.08499134 ..., -0.14874291  0.20775151
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  -0.24478977]
 [ 0.0504352  -0.01968318 -0.07725213 ...,  0.040636    0.45236278
   0.17945943]]
Progress: 15.5% ... Training loss: 0.263 ... Validation loss: 0.431[[ 0.33341609]
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[[ 0.04954255 -0.15636342  0.08156369 ..., -0.14917747  0.21120935
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 [-0.18541831 -0.19900232 -0.14132808 ...,  0.09818016 -0.08074864
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  -0.24550267]
 [ 0.05130095 -0.02045912 -0.07936644 ...,  0.04037229  0.45473541
   0.17711352]]
Progress: 15.5% ... Training loss: 0.287 ... Validation loss: 0.458[[ 0.3094487 ]
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[[ 0.04773389 -0.15486395  0.08570137 ..., -0.14872283  0.2068251
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   0.17852324]]
Progress: 15.5% ... Training loss: 0.279 ... Validation loss: 0.444[[ 0.32284961]
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[[ 0.04820553 -0.15532688  0.0844931  ..., -0.14890748  0.20833092
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   0.17826893]]
Progress: 15.5% ... Training loss: 0.259 ... Validation loss: 0.430[[ 0.31715584]
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[[ 0.04742181 -0.15465032  0.08649514 ..., -0.14865806  0.20623203
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  -0.24558936]
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   0.17869156]]
Progress: 15.5% ... Training loss: 0.263 ... Validation loss: 0.431[[ 0.32835224]
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[[ 0.04841274 -0.15559512  0.08399776 ..., -0.14897526  0.20902739
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  -0.24523496]
 [ 0.05082218 -0.02003744 -0.07845182 ...,  0.04050507  0.45483378
   0.17814824]]
Progress: 15.5% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.31224172]
 [-0.2915597 ]
 [-0.79383224]
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 [ 1.58690032]
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[[ 0.04728714 -0.15461705  0.08684557 ..., -0.14865667  0.20610918
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  -0.24470562]
 [ 0.05048123 -0.01972636 -0.07772344 ...,  0.04060643  0.45430104
   0.17898645]]
Progress: 15.5% ... Training loss: 0.275 ... Validation loss: 0.443[[ 0.32823002]
 [-0.27759999]
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 [ 1.59549469]
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[[ 0.04827075 -0.15555183  0.08447229 ..., -0.14898751  0.20882479
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 [-0.18595102 -0.19857706 -0.1401264  ...,  0.09830383 -0.08224171
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  -0.24566333]
 [ 0.05129326 -0.02049448 -0.07969195 ...,  0.04033776  0.45644658
   0.17690874]]
Progress: 15.5% ... Training loss: 0.265 ... Validation loss: 0.441[[ 0.3201453 ]
 [-0.28551855]
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[[ 0.04775457 -0.15510882  0.0857309  ..., -0.14885428  0.20732006
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   0.17710425]]
Progress: 15.5% ... Training loss: 0.261 ... Validation loss: 0.433[[ 0.32391019]
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   0.17675412]]
Progress: 15.5% ... Training loss: 0.260 ... Validation loss: 0.436[[ 0.32009714]
 [-0.28624833]
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[[ 0.04741732 -0.15483074  0.08634315 ..., -0.14875833  0.2060929
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   0.17638571]]
Progress: 15.5% ... Training loss: 0.263 ... Validation loss: 0.436[[ 0.32180753]
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[[ 0.04789847 -0.1552451   0.08524153 ..., -0.14889395  0.20749165
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 [ 0.05166975 -0.02078545 -0.08078625 ...,  0.04023364  0.45829565
   0.17574689]]
Progress: 15.5% ... Training loss: 0.261 ... Validation loss: 0.434[[ 0.32692285]
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[[ 0.04874291 -0.15602164  0.08320646 ..., -0.1491536   0.20964276
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 [ 0.05183315 -0.02094431 -0.08119935 ...,  0.0401829   0.4588564
   0.17510399]]
Progress: 15.5% ... Training loss: 0.266 ... Validation loss: 0.436[[ 0.3129398 ]
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[[ 0.04798454 -0.15532321  0.0850534  ..., -0.14892941  0.20788119
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 [-0.18556824 -0.19895642 -0.14117691 ...,  0.0981685  -0.08145804
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 [ 0.05154847 -0.02068932 -0.08047519 ...,  0.04027195  0.45827611
   0.17583447]]
Progress: 15.5% ... Training loss: 0.274 ... Validation loss: 0.445[[ 0.32209624]
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[[ 0.0476643  -0.15501573  0.08587452 ..., -0.14882022  0.20703122
  -0.17954461]
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 ..., 
 [-0.18555784 -0.19897305 -0.14116578 ...,  0.09816924 -0.08138154
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 [ 0.05179644 -0.02091935 -0.08112169 ...,  0.04018758  0.45909396
   0.17513854]]
Progress: 15.5% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.31971385]
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[[ 0.04701933 -0.15446508  0.08746909 ..., -0.14863514  0.20543329
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 ..., 
 [-0.18577623 -0.19878834 -0.14064636 ...,  0.09823228 -0.08194905
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  -0.24492984]
 [ 0.05160959 -0.02074272 -0.08066614 ...,  0.04024749  0.45905119
   0.17568075]]
Progress: 15.6% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.32437141]
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[[ 0.04687868 -0.15436787  0.08763143 ..., -0.14860138  0.20534111
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 [-0.18559293 -0.1989529  -0.14101767 ...,  0.09817662 -0.08145758
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 [ 0.05187817 -0.02097435 -0.0814185  ...,  0.0401768   0.46001949
   0.17477114]]
Progress: 15.6% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.32278972]
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   0.17438347]]
Progress: 15.6% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.31738067]
 [-0.28690597]
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 [ 1.59233891]
 [ 0.37514296]
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[[ 0.04626148 -0.15380704  0.08906359 ..., -0.14841604  0.20399028
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  -0.2449762 ]
 [ 0.0514612  -0.02057318 -0.08062366 ...,  0.04030716  0.45963901
   0.17568064]]
Progress: 15.6% ... Training loss: 0.262 ... Validation loss: 0.432[[ 0.32841542]
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[[ 0.04728504 -0.15471828  0.08652103 ..., -0.14873504  0.20699815
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  -0.24526419]
 [ 0.05172508 -0.02079728 -0.08132211 ...,  0.04022525  0.4605199
   0.1748672 ]]
Progress: 15.6% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.31626573]
 [-0.29056249]
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 [ 1.59101938]
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[[ 0.04646517 -0.1540506   0.08854789 ..., -0.14852105  0.20450476
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  -0.24435704]
 [ 0.05172176 -0.02079707 -0.08128567 ...,  0.04022096  0.46084013
   0.17500284]]
Progress: 15.6% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.31980405]
 [-0.28618821]
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[[ 0.04645477 -0.15403985  0.08866686 ..., -0.14851772  0.20453928
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  -0.24421748]
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   0.17471332]]
Progress: 15.6% ... Training loss: 0.260 ... Validation loss: 0.430[[ 0.32556604]
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[[ 0.0467201  -0.15426679  0.08802691 ..., -0.14859069  0.20545356
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  -0.24494787]
 [ 0.05155585 -0.02058695 -0.08091989 ...,  0.04029838  0.46105283
   0.17539938]]
Progress: 15.6% ... Training loss: 0.260 ... Validation loss: 0.433[[ 0.31773197]
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[[ 0.0459303  -0.15353463  0.08995852 ..., -0.14836033  0.20363247
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  -0.24428242]
 [ 0.05175908 -0.02075487 -0.08136214 ...,  0.04024204  0.46168976
   0.17479066]]
Progress: 15.6% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.31837042]
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[[ 0.04547134 -0.15309006  0.09108072 ..., -0.14821965  0.20319889
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   0.17393562]]
Progress: 15.6% ... Training loss: 0.259 ... Validation loss: 0.427[[ 0.31879856]
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[[ 0.04557074 -0.15319261  0.09105312 ..., -0.14825146  0.20368101
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   0.17430916]]
Progress: 15.6% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.31587409]
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[[ 0.04529604 -0.15292207  0.09164934 ..., -0.14817499  0.20325192
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 [-0.18620768 -0.1984586  -0.1396023  ...,  0.09835748 -0.08345245
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  -0.24440469]
 [ 0.05127776 -0.02026935 -0.08023663 ...,  0.04038455  0.46148569
   0.1755218 ]]
Progress: 15.6% ... Training loss: 0.261 ... Validation loss: 0.430[[ 0.31903425]
 [-0.28196509]
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[[ 0.04528094 -0.15289491  0.09176708 ..., -0.14815663  0.20308615
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 [ 0.05159245 -0.02055269 -0.08104065 ...,  0.04028565  0.46218228
   0.17470662]]
Progress: 15.6% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.31814487]
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[[ 0.04482798 -0.15248509  0.09293059 ..., -0.1480346   0.20207285
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   0.17548202]]
Progress: 15.6% ... Training loss: 0.260 ... Validation loss: 0.430[[ 0.31947579]
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[[ 0.04447821 -0.15210608  0.09392558 ..., -0.1478949   0.20149292
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  -0.24534539]
 [ 0.05108186 -0.020057   -0.07978486 ...,  0.04046148  0.46161743
   0.17591563]]
Progress: 15.6% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32275925]
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[[ 0.04501738 -0.1525853   0.09262754 ..., -0.1480664   0.20312526
  -0.172369  ]
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 [-0.18614502 -0.19853667 -0.13967568 ...,  0.09833744 -0.08344888
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   0.17630869]]
Progress: 15.7% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.32003223]
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[[ 0.04451495 -0.15215016  0.09384623 ..., -0.14792235  0.20180422
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   0.17609696]]
Progress: 15.7% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.31556461]
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[[ 0.04401372 -0.15168119  0.09513587 ..., -0.14776433  0.20021069
  -0.16982974]
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 [ 0.05103823 -0.01997571 -0.07986125 ...,  0.04048463  0.46206321
   0.17585177]]
Progress: 15.7% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.32103805]
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[[ 0.04462426 -0.15215882  0.09369565 ..., -0.14792339  0.20179375
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   0.17447198]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32017717]
 [-0.28020965]
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[[ 0.0452046  -0.15265577  0.09227865 ..., -0.14808008  0.20399487
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  -0.24513772]
 [ 0.05141628 -0.02024262 -0.08095417 ...,  0.04039108  0.46401709
   0.17447498]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.31778554]
 [-0.28325448]
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[[ 0.04493885 -0.15243275  0.09293705 ..., -0.14802277  0.20325516
  -0.17213897]
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  -0.24465049]
 [ 0.05106014 -0.0199271  -0.08011634 ...,  0.04049895  0.46324373
   0.17541174]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.427[[ 0.31933018]
 [-0.28314253]
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 [ 1.59928306]
 [ 0.37888324]
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[[ 0.04488758 -0.1524203   0.09295356 ..., -0.14803036  0.20353558
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  -0.24463546]
 [ 0.05083821 -0.01971765 -0.07969872 ...,  0.04056112  0.46314209
   0.17596834]]
Progress: 15.7% ... Training loss: 0.258 ... Validation loss: 0.427[[ 0.32154999]
 [-0.28044238]
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[[ 0.04523942 -0.15272566  0.09225587 ..., -0.14812399  0.20418815
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 [-0.18521882 -0.19936441 -0.1418941  ...,  0.09805169 -0.08130221
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  -0.24519698]
 [ 0.05094159 -0.01979341 -0.07995756 ...,  0.04053683  0.46355087
   0.175724  ]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.426[[ 0.31822277]
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[[ 0.0448621  -0.15242508  0.09321302 ..., -0.14802484  0.20305113
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  -0.24527961]
 [ 0.05080138 -0.01966545 -0.07962249 ...,  0.04058412  0.4634719
   0.17617924]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.33100128]
 [-0.27270574]
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[[ 0.04575222 -0.15323634  0.09122658 ..., -0.14830858  0.20548575
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  -0.24498482]
 [ 0.05101523 -0.01985646 -0.08015192 ...,  0.04051789  0.4642283
   0.17574852]]
Progress: 15.7% ... Training loss: 0.278 ... Validation loss: 0.444[[ 0.32068885]
 [-0.2831097 ]
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[[ 0.04467883 -0.15229331  0.09363138 ..., -0.14801831  0.20314208
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  -0.24524311]
 [ 0.05061937 -0.01949065 -0.07924175 ...,  0.04063218  0.46383867
   0.17650593]]
Progress: 15.7% ... Training loss: 0.259 ... Validation loss: 0.426[[ 0.32231046]
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[[ 0.04524424 -0.15275263  0.0921845  ..., -0.14816381  0.20477627
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  -0.24448803]
 [ 0.05074411 -0.01959244 -0.07965342 ...,  0.04060167  0.46435056
   0.17606523]]
Progress: 15.7% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.31685244]
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[[ 0.04477492 -0.15229606  0.09333766 ..., -0.14802168  0.20431318
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 [-0.18607139 -0.19865742 -0.13988996 ...,  0.09827586 -0.08365171
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  -0.24387427]
 [ 0.0503361  -0.01915096 -0.0786959  ...,  0.04074159  0.46432953
   0.17696106]]
Progress: 15.7% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.32493162]
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[[ 0.04587368 -0.15326713  0.09076732 ..., -0.14833517  0.2071728
  -0.17440795]
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 [-0.18592322 -0.19879063 -0.14026222 ...,  0.09823262 -0.0832839
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  -0.24417704]
 [ 0.05086869 -0.01961532 -0.08000711 ...,  0.04059356  0.46608729
   0.1756675 ]]
Progress: 15.7% ... Training loss: 0.268 ... Validation loss: 0.428[[ 0.31204969]
 [-0.29220106]
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[[ 0.04474961 -0.15223766  0.09343668 ..., -0.14804012  0.20444392
  -0.17212101]
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   0.11110316]
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 [-0.18578324 -0.19892029 -0.14056661 ...,  0.09819138 -0.08311601
  -0.06442467]
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  -0.24370485]
 [ 0.05046377 -0.01922567 -0.0790598  ...,  0.04070529  0.46534604
   0.17651784]]
Progress: 15.7% ... Training loss: 0.267 ... Validation loss: 0.434[[ 0.33095917]
 [-0.27595056]
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[[ 0.04566188 -0.1530913   0.09117241 ..., -0.14831699  0.20727066
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 [ 0.04268849  0.04441994  0.09671811 ..., -0.24603283 -0.00871158
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 ..., 
 [-0.18545315 -0.19922401 -0.14141285 ...,  0.09809252 -0.08226555
  -0.06534465]
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  -0.24418167]
 [ 0.0508723  -0.01961984 -0.07997719 ...,  0.04057517  0.46677502
   0.17561409]]
Progress: 15.8% ... Training loss: 0.285 ... Validation loss: 0.442[[ 0.31682928]
 [-0.2894529 ]
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[[ 0.04504071 -0.15259034  0.09245459 ..., -0.14816734  0.20578722
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   0.17540234]]
Progress: 15.8% ... Training loss: 0.261 ... Validation loss: 0.425[[ 0.32445581]
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   0.17546082]]
Progress: 15.8% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.31493458]
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[[ 0.04549204 -0.15296457  0.0916811  ..., -0.14828843  0.20682612
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   0.17495228]]
Progress: 15.8% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.32389445]
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   0.17344989]]
Progress: 15.8% ... Training loss: 0.262 ... Validation loss: 0.426[[ 0.32257843]
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   0.17249462]]
Progress: 15.8% ... Training loss: 0.261 ... Validation loss: 0.424[[ 0.31392576]
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   0.17387628]]
Progress: 15.8% ... Training loss: 0.267 ... Validation loss: 0.433[[ 0.32387598]
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   0.1739148 ]]
Progress: 15.8% ... Training loss: 0.262 ... Validation loss: 0.423[[ 0.30910317]
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   0.17603503]]
Progress: 15.8% ... Training loss: 0.277 ... Validation loss: 0.446[[ 0.32245935]
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 [ 0.05044959 -0.01911871 -0.0793087  ...,  0.04072688  0.46776241
   0.17628774]]
Progress: 15.8% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.31774485]
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[[ 0.04527002 -0.15289053  0.09244859 ..., -0.1483366   0.20642139
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   0.17590662]]
Progress: 15.8% ... Training loss: 0.259 ... Validation loss: 0.427[[ 0.32079289]
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[[ 0.0455219  -0.15313882  0.09184212 ..., -0.14840063  0.20725583
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   0.17618808]]
Progress: 15.8% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.32457979]
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[[ 0.04599323 -0.15355472  0.09066561 ..., -0.14852669  0.20828277
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   0.17534043]]
Progress: 15.8% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.31725863]
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[[ 0.04578501 -0.15338579  0.09114233 ..., -0.14845795  0.20756114
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   0.17579804]]
Progress: 15.8% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.31644067]
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[[ 0.04530974 -0.15293915  0.09232378 ..., -0.14831486  0.20642521
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   0.17589242]]
Progress: 15.8% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.31653082]
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[[ 0.04590635 -0.15345466  0.09109644 ..., -0.14847257  0.20854315
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   0.17574233]]
Progress: 15.9% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.32490255]
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   0.17520938]]
Progress: 15.9% ... Training loss: 0.264 ... Validation loss: 0.429[[ 0.32258795]
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   0.17591267]]
Progress: 15.9% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32240618]
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   0.17532332]]
Progress: 15.9% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.31010981]
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   0.17547584]]
Progress: 15.9% ... Training loss: 0.273 ... Validation loss: 0.440[[ 0.32016694]
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   0.17546867]]
Progress: 15.9% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.32835594]
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   0.17585359]]
Progress: 15.9% ... Training loss: 0.272 ... Validation loss: 0.441[[ 0.32170405]
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   0.1760933 ]]
Progress: 15.9% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.31979193]
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   0.17535733]]
Progress: 15.9% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.32150218]
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[[ 0.04705986 -0.15452354  0.089239   ..., -0.14883228  0.21145907
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   0.17665268]]
Progress: 15.9% ... Training loss: 0.258 ... Validation loss: 0.429[[ 0.31649601]
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[[ 0.04613029 -0.15366596  0.09145948 ..., -0.14857121  0.20892091
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   0.17516736]]
Progress: 15.9% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.32356691]
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[[ 0.04596522 -0.15348651  0.09192819 ..., -0.14850737  0.20884138
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   0.17505933]]
Progress: 15.9% ... Training loss: 0.260 ... Validation loss: 0.433[[ 0.32144317]
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[[ 0.04611353 -0.15357161  0.09155104 ..., -0.14854565  0.20951916
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   0.17647205]]
Progress: 15.9% ... Training loss: 0.259 ... Validation loss: 0.431[[ 0.31035046]
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[[ 0.04557934 -0.15306654  0.09292045 ..., -0.14839217  0.2083957
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   0.17708123]]
Progress: 15.9% ... Training loss: 0.270 ... Validation loss: 0.436[[ 0.3197643 ]
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[[ 0.04633596 -0.15375044  0.09110695 ..., -0.14862872  0.21005773
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   0.17668873]]
Progress: 15.9% ... Training loss: 0.259 ... Validation loss: 0.431[[ 0.32333158]
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[[ 0.0465484  -0.15395777  0.09070989 ..., -0.14870016  0.21065952
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   0.17538064]]
Progress: 16.0% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.31607651]
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[[ 0.04617701 -0.15362559  0.09176576 ..., -0.14858921  0.2095219
  -0.17295004]
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   0.17663265]]
Progress: 16.0% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.32383352]
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   0.1750638 ]]
Progress: 16.0% ... Training loss: 0.268 ... Validation loss: 0.440[[ 0.31993459]
 [-0.28559884]
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 [ 1.61107661]
 [ 0.38020796]
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[[ 0.04688348 -0.1542781   0.08985978 ..., -0.14883884  0.21170002
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   0.17536393]]
Progress: 16.0% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.31198507]
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 [ 1.60291139]
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[[ 0.04599743 -0.1534402   0.09207624 ..., -0.14856928  0.20953457
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  -0.24632347]
 [ 0.04989487 -0.0182868  -0.07844652 ...,  0.04095706  0.47310124
   0.17641086]]
Progress: 16.0% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.31793766]
 [-0.28738326]
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[[ 0.04701524 -0.15439434  0.08965458 ..., -0.14888924  0.21210867
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   0.1761298 ]]
Progress: 16.0% ... Training loss: 0.259 ... Validation loss: 0.427[[ 0.31433644]
 [-0.28976682]
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 [ 1.60744025]
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[[ 0.04662722 -0.1540362   0.09064821 ..., -0.14876312  0.21138454
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  -0.24576135]
 [ 0.04967286 -0.01805366 -0.07790753 ...,  0.04103117  0.4728342
   0.17713406]]
Progress: 16.0% ... Training loss: 0.258 ... Validation loss: 0.424[[ 0.31130144]
 [-0.29037288]
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[[ 0.04645591 -0.15381127  0.0910458  ..., -0.14869756  0.21111159
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   0.17711838]]
Progress: 16.0% ... Training loss: 0.259 ... Validation loss: 0.422[[ 0.31487638]
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[[ 0.04691604 -0.15425028  0.08999299 ..., -0.14882033  0.21215424
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   0.17609245]]
Progress: 16.0% ... Training loss: 0.259 ... Validation loss: 0.423[[ 0.31988747]
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[[ 0.0472911  -0.15458619  0.08920544 ..., -0.14892655  0.21324417
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 [ 0.05027108 -0.0185854  -0.07947731 ...,  0.04084781  0.47464555
   0.17505313]]
Progress: 16.0% ... Training loss: 0.267 ... Validation loss: 0.427[[ 0.30539044]
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[[ 0.0457074  -0.15319981  0.09319508 ..., -0.14850108  0.20901104
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  -0.24407221]
 [ 0.05023826 -0.01856558 -0.07933374 ...,  0.04085513  0.47472273
   0.17519383]]
Progress: 16.0% ... Training loss: 0.273 ... Validation loss: 0.436[[ 0.32609926]
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[[ 0.04747607 -0.15491512  0.0889519  ..., -0.14909122  0.21379889
  -0.17639265]
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 [ 0.05048401 -0.01878257 -0.07995676 ...,  0.04077815  0.47542643
   0.17440133]]
Progress: 16.0% ... Training loss: 0.285 ... Validation loss: 0.448[[ 0.30913788]
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[[ 0.04707607 -0.15457466  0.08981781 ..., -0.1489912   0.21264419
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 [-0.18631161 -0.19881836 -0.13982    ...,  0.09815357 -0.08711342
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  -0.2441342 ]
 [ 0.0505933  -0.01886297 -0.08033154 ...,  0.0407597   0.47575985
   0.17397696]]
Progress: 16.0% ... Training loss: 0.260 ... Validation loss: 0.422[[ 0.31187643]
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[[ 0.04710772 -0.15463624  0.08988772 ..., -0.14901262  0.21273634
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  -0.243457  ]
 [ 0.05109856 -0.01932959 -0.08164988 ...,  0.04060676  0.47732213
   0.17253065]]
Progress: 16.0% ... Training loss: 0.258 ... Validation loss: 0.423[[ 0.30765724]
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[[ 0.04639882 -0.15394172  0.0917414  ..., -0.14879464  0.21119078
  -0.1738244 ]
 [ 0.04277947  0.0443313   0.09583002 ..., -0.24609277 -0.00703075
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 [ 0.05107431 -0.01929776 -0.08154898 ...,  0.04062251  0.47742399
   0.17249718]]
Progress: 16.0% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.32103942]
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[[ 0.04677462 -0.15423622  0.09074046 ..., -0.1489169   0.21257689
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   0.17208506]]
Progress: 16.1% ... Training loss: 0.266 ... Validation loss: 0.433[[ 0.31049025]
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[[ 0.04623866 -0.15379487  0.09196841 ..., -0.14877667  0.21124534
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 [ 0.05110862 -0.01928945 -0.08169807 ...,  0.04062582  0.47824499
   0.17233418]]
Progress: 16.1% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.31055253]
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[[ 0.04633655 -0.15388284  0.09172741 ..., -0.14880038  0.21171162
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   0.17284021]]
Progress: 16.1% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.31106987]
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[[ 0.04652861 -0.15409402  0.0913475  ..., -0.14886969  0.21225068
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   0.17224598]]
Progress: 16.1% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.31501345]
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   0.17223867]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.31443455]
 [-0.28691998]
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[[ 0.04625225 -0.15383103  0.09243209 ..., -0.14877779  0.21158852
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   0.17283869]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.31472988]
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[[ 0.04616451 -0.15375383  0.09284164 ..., -0.14875055  0.21128518
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  -0.24522973]
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   0.17309407]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.429[[ 0.30576373]
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[[ 0.04581317 -0.15341048  0.09375482 ..., -0.14863717  0.21029821
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   0.17344012]]
Progress: 16.1% ... Training loss: 0.274 ... Validation loss: 0.436[[ 0.31635615]
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[[ 0.04666305 -0.15422661  0.09174553 ..., -0.14892056  0.21274266
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 [ 0.05088415 -0.01907267 -0.0812272  ...,  0.04069272  0.47852763
   0.17255469]]
Progress: 16.1% ... Training loss: 0.259 ... Validation loss: 0.432[[ 0.31047468]
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[[ 0.04593866 -0.15350267  0.09359127 ..., -0.14870511  0.21125206
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   0.17266432]]
Progress: 16.1% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.31008134]
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[[ 0.04565936 -0.15321298  0.09427625 ..., -0.14859581  0.21032381
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   0.17333822]]
Progress: 16.1% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.31194776]
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[[ 0.04597623 -0.15349126  0.09364587 ..., -0.14869908  0.21148687
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   0.17465435]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.30982181]
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[[ 0.04611666 -0.15363374  0.09336371 ..., -0.14874181  0.21176707
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  -0.24690502]
 [ 0.04990706 -0.0180892  -0.0788716  ...,  0.0410161   0.47692592
   0.1752092 ]]
Progress: 16.1% ... Training loss: 0.260 ... Validation loss: 0.430[[ 0.31105343]
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[[ 0.04645985 -0.15393936  0.09267525 ..., -0.14886158  0.21317566
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 [-0.1869533  -0.1983183  -0.13839564 ...,  0.09826615 -0.0892896
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 [ 0.04975698 -0.01792497 -0.07853487 ...,  0.04107343  0.47700759
   0.17532427]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.31009033]
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[[ 0.04609744 -0.15355938  0.09364769 ..., -0.14873841  0.21257863
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   0.17668965]]
Progress: 16.1% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.32293814]
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[[ 0.04757556 -0.15500394  0.09012086 ..., -0.14920673  0.21638899
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Progress: 16.2% ... Training loss: 0.281 ... Validation loss: 0.452[[ 0.30543042]
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[[ 0.04621482 -0.1537717   0.09324971 ..., -0.14883506  0.21303365
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   0.17666815]]
Progress: 16.2% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.3187108 ]
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   0.1753084 ]]
Progress: 16.2% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.3062485 ]
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   0.17600238]]
Progress: 16.2% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.31916636]
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   0.17398481]]
Progress: 16.2% ... Training loss: 0.274 ... Validation loss: 0.436[[ 0.29105164]
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   0.17443913]]
Progress: 16.2% ... Training loss: 0.319 ... Validation loss: 0.487[[ 0.32784083]
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   0.1725359 ]]
Progress: 16.2% ... Training loss: 0.311 ... Validation loss: 0.476[[ 0.29650211]
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   0.17567433]]
Progress: 16.2% ... Training loss: 0.288 ... Validation loss: 0.457[[ 0.31956543]
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[[ 0.04628504 -0.15452459  0.09203708 ..., -0.14931289  0.21489514
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   0.17539189]]
Progress: 16.2% ... Training loss: 0.280 ... Validation loss: 0.438[[ 0.30285981]
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[[ 0.04466535 -0.15301615  0.0959793  ..., -0.1488723   0.21117521
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   0.17541641]]
Progress: 16.2% ... Training loss: 0.264 ... Validation loss: 0.429[[ 0.30790676]
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   0.17419555]]
Progress: 16.2% ... Training loss: 0.258 ... Validation loss: 0.422[[ 0.31601004]
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[[ 0.04477133 -0.1531458   0.09590181 ..., -0.14890087  0.2113158
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   0.17429136]]
Progress: 16.2% ... Training loss: 0.266 ... Validation loss: 0.426[[ 0.29349994]
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[[ 0.0441513  -0.15262078  0.09735043 ..., -0.14874175  0.20970626
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   0.17613051]]
Progress: 16.2% ... Training loss: 0.304 ... Validation loss: 0.467[[ 0.31437437]
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[[ 0.04545381 -0.153962    0.09413504 ..., -0.14920425  0.21367584
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   0.17456771]]
Progress: 16.2% ... Training loss: 0.262 ... Validation loss: 0.426[[ 0.30283918]
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[[ 0.04471576 -0.15329467  0.09589681 ..., -0.14900718  0.21163254
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 [ 0.04901327 -0.01731136 -0.0783238  ...,  0.04111949  0.4802782
   0.17451287]]
Progress: 16.2% ... Training loss: 0.265 ... Validation loss: 0.431[[ 0.31203758]
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   0.17537665]]
Progress: 16.3% ... Training loss: 0.258 ... Validation loss: 0.424[[ 0.31512035]
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   0.17478367]]
Progress: 16.3% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.30730137]
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[[ 0.04514544 -0.15376345  0.09507075 ..., -0.14915372  0.21252279
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   0.17446911]]
Progress: 16.3% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.32653271]
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[[ 0.04640851 -0.15497648  0.09188426 ..., -0.14954371  0.21569662
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   0.17253283]]
Progress: 16.3% ... Training loss: 0.294 ... Validation loss: 0.463[[ 0.30473454]
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[[ 0.0447165  -0.15348437  0.09575944 ..., -0.14911273  0.21177594
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   0.17360369]]
Progress: 16.3% ... Training loss: 0.266 ... Validation loss: 0.431[[ 0.31805244]
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[[ 0.04574425 -0.15442037  0.09327924 ..., -0.14943922  0.21506903
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   0.17198501]]
Progress: 16.3% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.31832184]
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[[ 0.04599993 -0.15462829  0.09269038 ..., -0.14950543  0.21599153
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   0.17285277]]
Progress: 16.3% ... Training loss: 0.272 ... Validation loss: 0.439[[ 0.31095102]
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   0.17366746]]
Progress: 16.3% ... Training loss: 0.257 ... Validation loss: 0.424[[ 0.30778301]
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   0.1742246 ]]
Progress: 16.3% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.30491322]
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[[ 0.04448967 -0.15322999  0.09639282 ..., -0.14904938  0.21231913
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 [ 0.04890304 -0.01716267 -0.07802068 ...,  0.04115105  0.48261354
   0.17416728]]
Progress: 16.3% ... Training loss: 0.264 ... Validation loss: 0.430[[ 0.31894446]
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[[ 0.0457182  -0.1544305   0.09338955 ..., -0.149443    0.21553838
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 [ 0.04979479 -0.01802308 -0.08026438 ...,  0.04087223  0.48538014
   0.17158968]]
Progress: 16.3% ... Training loss: 0.269 ... Validation loss: 0.440[[ 0.3075789 ]
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[[ 0.04496034 -0.15378999  0.09509316 ..., -0.14924983  0.21324695
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   0.17190398]]
Progress: 16.3% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.31555559]
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[[ 0.0453357  -0.15415539  0.09406691 ..., -0.14937249  0.21468297
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   0.17169421]]
Progress: 16.3% ... Training loss: 0.258 ... Validation loss: 0.430[[ 0.30827616]
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[[ 0.04475489 -0.15359619  0.09572749 ..., -0.14920862  0.21352829
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 [ 0.04960669 -0.01785251 -0.07994336 ...,  0.04091251  0.48535024
   0.17195351]]
Progress: 16.3% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.30142932]
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[[ 0.04404795 -0.15288206  0.09753455 ..., -0.14897716  0.21206798
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 [ 0.04346739  0.04363885  0.09365851 ..., -0.24636614 -0.00343431
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   0.17197328]]
Progress: 16.3% ... Training loss: 0.276 ... Validation loss: 0.434[[ 0.31389433]
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[[ 0.04467995 -0.15352084  0.09586224 ..., -0.14919798  0.2139004
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   0.17122127]]
Progress: 16.4% ... Training loss: 0.258 ... Validation loss: 0.427[[ 0.3072798 ]
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   0.17133539]]
Progress: 16.4% ... Training loss: 0.259 ... Validation loss: 0.424[[ 0.31713944]
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[[ 0.04533075 -0.15413259  0.09407758 ..., -0.14940038  0.21597135
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  -0.2444694 ]
 [ 0.04979728 -0.01798579 -0.0805577  ...,  0.04086527  0.48701157
   0.17120717]]
Progress: 16.4% ... Training loss: 0.268 ... Validation loss: 0.432[[ 0.29917216]
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[[ 0.0442866  -0.15315058  0.09681195 ..., -0.14909546  0.21344201
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  -0.24398382]
 [ 0.04901368 -0.01723614 -0.0787763  ...,  0.04108493  0.48562536
   0.17312648]]
Progress: 16.4% ... Training loss: 0.277 ... Validation loss: 0.436[[ 0.31380452]
 [-0.28600018]
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 [-0.75077613]
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[[ 0.04512096 -0.15398073  0.09483317 ..., -0.14936757  0.21553875
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  -0.24621758]
 [ 0.04900991 -0.01722485 -0.0787508  ...,  0.04109159  0.48564006
   0.17311991]]
Progress: 16.4% ... Training loss: 0.261 ... Validation loss: 0.429[[ 0.30289138]
 [-0.29515681]
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 [-0.76047167]
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 [ 1.61163284]
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[[ 0.04451349 -0.15337675  0.0965061  ..., -0.14917373  0.21402953
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   0.17472583]]
Progress: 16.4% ... Training loss: 0.264 ... Validation loss: 0.429[[ 0.3051327 ]
 [-0.29399704]
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   0.17539699]]
Progress: 16.4% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.32295997]
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[[ 0.0463599  -0.15516225  0.09210258 ..., -0.14974803  0.21893315
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   0.1734615 ]]
Progress: 16.4% ... Training loss: 0.284 ... Validation loss: 0.462[[ 0.30576688]
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[[ 0.04465111 -0.15363578  0.09622432 ..., -0.14930744  0.2146842
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   0.17426386]]
Progress: 16.4% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.31945665]
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[[ 0.04575089 -0.15467139  0.09348655 ..., -0.14963259  0.2173799
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 [ 0.04877903 -0.01698553 -0.07823045 ...,  0.04114043  0.48627837
   0.17347352]]
Progress: 16.4% ... Training loss: 0.272 ... Validation loss: 0.446[[ 0.29893204]
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[[ 0.04451824 -0.15355177  0.09625935 ..., -0.14929242  0.21419781
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 [ 0.0484253  -0.01666263 -0.07741629 ...,  0.04123658  0.48566687
   0.17431707]]
Progress: 16.4% ... Training loss: 0.278 ... Validation loss: 0.438[[ 0.3121179 ]
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[[ 0.04511891 -0.15421776  0.09503942 ..., -0.14950024  0.21586036
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 [ 0.04839308 -0.01659395 -0.07745229 ...,  0.04126328  0.4859624
   0.17433403]]
Progress: 16.4% ... Training loss: 0.257 ... Validation loss: 0.429[[ 0.30935168]
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[[ 0.04538595 -0.15446718  0.09438536 ..., -0.14958278  0.21671607
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  -0.24781696]
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   0.17449998]]
Progress: 16.4% ... Training loss: 0.258 ... Validation loss: 0.427[[ 0.30987132]
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[[ 0.04509681 -0.15423597  0.09516628 ..., -0.14950009  0.21627828
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   0.17473953]]
Progress: 16.4% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.31328529]
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[[ 0.04493754 -0.154081    0.09563037 ..., -0.14944002  0.21590459
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   0.17441249]]
Progress: 16.4% ... Training loss: 0.257 ... Validation loss: 0.428[[ 0.30814836]
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[[ 0.04385838 -0.1531209   0.09824816 ..., -0.14912836  0.21315275
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   0.17517763]]
Progress: 16.5% ... Training loss: 0.265 ... Validation loss: 0.433[[ 0.31081437]
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[[ 0.04409459 -0.15332252  0.0977254  ..., -0.14919668  0.21379752
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   0.17590203]]
Progress: 16.5% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.31515875]
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[[ 0.04422349 -0.15344858  0.09745467 ..., -0.14923738  0.21406675
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   0.17539963]]
Progress: 16.5% ... Training loss: 0.258 ... Validation loss: 0.430[[ 0.30965351]
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[[ 0.04385024 -0.15307499  0.09841529 ..., -0.14912871  0.21326351
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   0.17642086]]
Progress: 16.5% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.30834422]
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[[ 0.04396491 -0.15317345  0.09823196 ..., -0.14916394  0.21341492
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 [ 0.04739778 -0.01552781 -0.07525644 ...,  0.04162394  0.4856406
   0.17659423]]
Progress: 16.5% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.31666433]
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[[ 0.04480447 -0.15393892  0.09620345 ..., -0.14940386  0.21567038
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   0.17538839]]
Progress: 16.5% ... Training loss: 0.264 ... Validation loss: 0.435[[ 0.31217274]
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[[ 0.04444086 -0.15359926  0.09719142 ..., -0.14930827  0.21499571
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   0.17613592]]
Progress: 16.5% ... Training loss: 0.257 ... Validation loss: 0.427[[ 0.31772677]
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   0.17463167]]
Progress: 16.5% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.31468262]
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[[ 0.04411545 -0.15327433  0.09791019 ..., -0.1492301   0.21407599
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   0.17519271]]
Progress: 16.5% ... Training loss: 0.258 ... Validation loss: 0.431[[ 0.31529802]
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[[ 0.04413738 -0.15329069  0.09793731 ..., -0.14923718  0.21439699
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 [ 0.04733713 -0.01539281 -0.07514667 ...,  0.0416441   0.48676657
   0.17661962]]
Progress: 16.5% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.31136254]
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[[ 0.04416467 -0.15332041  0.09782284 ..., -0.14924664  0.2146954
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  -0.24566751]
 [ 0.04736479 -0.01540844 -0.07527551 ...,  0.04164069  0.48695135
   0.17651268]]
Progress: 16.5% ... Training loss: 0.257 ... Validation loss: 0.426[[ 0.30578081]
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[[ 0.0435697  -0.15274347  0.09928044 ..., -0.14907457  0.21316826
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 [-0.1859458  -0.19983449 -0.14171145 ...,  0.09759748 -0.08872035
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 [ 0.04723708 -0.01527782 -0.07490194 ...,  0.04168006  0.48680508
   0.17682119]]
Progress: 16.5% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.31815133]
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[[ 0.04444455 -0.15357603  0.09715383 ..., -0.14933316  0.21527127
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 [-0.18562341 -0.20013143 -0.14248512 ...,  0.09749693 -0.08790282
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  -0.24587279]
 [ 0.04779659 -0.01582104 -0.07630155 ...,  0.04150433  0.48856781
   0.1753282 ]]
Progress: 16.5% ... Training loss: 0.266 ... Validation loss: 0.440[[ 0.31384665]
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[[ 0.04397835 -0.1531448   0.09830957 ..., -0.14920352  0.21395698
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   0.17534371]]
Progress: 16.5% ... Training loss: 0.258 ... Validation loss: 0.431[[ 0.3160488 ]
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[[ 0.04387781 -0.15307808  0.09852401 ..., -0.14917633  0.21373751
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   0.17519009]]
Progress: 16.5% ... Training loss: 0.260 ... Validation loss: 0.433[[ 0.31125432]
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[[ 0.04356956 -0.15278534  0.09918466 ..., -0.14909869  0.21321294
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   0.17550634]]
Progress: 16.6% ... Training loss: 0.257 ... Validation loss: 0.427[[ 0.3158272 ]
 [-0.28247749]
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[[ 0.04385838 -0.15301682  0.09859168 ..., -0.14917968  0.21417703
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  -0.2458587 ]
 [ 0.04762341 -0.01560472 -0.075944   ...,  0.04156286  0.48902497
   0.17552979]]
Progress: 16.6% ... Training loss: 0.260 ... Validation loss: 0.434[[ 0.30739832]
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[[ 0.0433191  -0.15255631  0.09983249 ..., -0.14903624  0.21265894
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  -0.24583101]
 [ 0.04754942 -0.01553636 -0.07587301 ...,  0.04157291  0.48887089
   0.17555118]]
Progress: 16.6% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.31162546]
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[[ 0.0425154  -0.15179171  0.1020318  ..., -0.14879721  0.210546
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   0.17628717]]
Progress: 16.6% ... Training loss: 0.257 ... Validation loss: 0.432[[ 0.31386949]
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[[ 0.04309217 -0.15233118  0.10062003 ..., -0.14896876  0.21190857
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 [ 0.04758526 -0.01555171 -0.0758544  ...,  0.04156776  0.48930838
   0.17539946]]
Progress: 16.6% ... Training loss: 0.257 ... Validation loss: 0.434[[ 0.31941154]
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[[ 0.04414011 -0.15333517  0.09830346 ..., -0.14927487  0.21458808
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   0.17511796]]
Progress: 16.6% ... Training loss: 0.264 ... Validation loss: 0.440[[ 0.30626822]
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[[ 0.04308575 -0.15242658  0.10085096 ..., -0.14900652  0.21184488
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   0.17438958]]
Progress: 16.6% ... Training loss: 0.269 ... Validation loss: 0.439[[ 0.31885951]
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   0.17334238]]
Progress: 16.6% ... Training loss: 0.259 ... Validation loss: 0.439[[ 0.32131164]
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[[ 0.04494651 -0.15415634  0.09649291 ..., -0.14956899  0.21723717
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   0.17240216]]
Progress: 16.6% ... Training loss: 0.263 ... Validation loss: 0.442[[ 0.30813191]
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[[ 0.04434407 -0.15358664  0.09801691 ..., -0.14940074  0.21585636
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   0.17256226]]
Progress: 16.6% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.31008397]
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[[ 0.04480353 -0.15402736  0.09706847 ..., -0.14954875  0.21726449
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 [ 0.04879989 -0.01663507 -0.07882667 ...,  0.04124332  0.49384366
   0.17226448]]
Progress: 16.6% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.3077516 ]
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[[ 0.04462126 -0.15384709  0.09760377 ..., -0.14947606  0.21671387
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 [ 0.04809124 -0.01595243 -0.07708902 ...,  0.04145371  0.49219292
   0.17418204]]
Progress: 16.6% ... Training loss: 0.262 ... Validation loss: 0.431[[ 0.31936553]
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[[ 0.04540789 -0.15463938  0.09580118 ..., -0.14970958  0.21846489
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 [ 0.04817512 -0.01602122 -0.07726267 ...,  0.04143578  0.49252674
   0.17405072]]
Progress: 16.6% ... Training loss: 0.263 ... Validation loss: 0.444[[ 0.31421993]
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[[ 0.04554369 -0.15477417  0.09540774 ..., -0.14974388  0.21861169
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   0.17487375]]
Progress: 16.6% ... Training loss: 0.257 ... Validation loss: 0.430[[ 0.32431226]
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Progress: 16.6% ... Training loss: 0.282 ... Validation loss: 0.456[[ 0.299113  ]
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   0.17469271]]
Progress: 16.7% ... Training loss: 0.281 ... Validation loss: 0.445[[ 0.31207063]
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   0.17422292]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.31225679]
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   0.17451626]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.31070522]
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   0.17419968]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.3103908 ]
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   0.17433251]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.426[[ 0.30955487]
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   0.17415028]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.426[[ 0.3087597 ]
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   0.17368584]]
Progress: 16.7% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.31601573]
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   0.17240153]]
Progress: 16.7% ... Training loss: 0.261 ... Validation loss: 0.433[[ 0.30836596]
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   0.17382688]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.31422319]
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   0.17330944]]
Progress: 16.7% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.30824659]
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[[ 0.0440167  -0.153368    0.09928513 ..., -0.14932596  0.21680905
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   0.17281112]]
Progress: 16.7% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.32154994]
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[[ 0.04531304 -0.15458675  0.09598064 ..., -0.14971392  0.2202422
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   0.17240897]]
Progress: 16.7% ... Training loss: 0.276 ... Validation loss: 0.447[[ 0.30129335]
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[[ 0.04363214 -0.15312522  0.09978544 ..., -0.1492797   0.21642197
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   0.1734305 ]]
Progress: 16.7% ... Training loss: 0.276 ... Validation loss: 0.436[[ 0.31772783]
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[[ 0.04497384 -0.15448257  0.09641671 ..., -0.14973014  0.22008038
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   0.17236673]]
Progress: 16.7% ... Training loss: 0.263 ... Validation loss: 0.431[[ 0.31172226]
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[[ 0.04406298 -0.15366275  0.09861645 ..., -0.14947552  0.21748695
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   0.1718833 ]]
Progress: 16.7% ... Training loss: 0.256 ... Validation loss: 0.423[[ 0.30211984]
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[[ 0.04366741 -0.15327798  0.09962272 ..., -0.14935079  0.21658149
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  -0.24398081]
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   0.17356662]]
Progress: 16.8% ... Training loss: 0.274 ... Validation loss: 0.437[[ 0.32010613]
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[[ 0.04511685 -0.15470251  0.09612763 ..., -0.14982324  0.22043437
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 [ 0.04811577 -0.01590039 -0.07800105 ...,  0.04144438  0.498075
   0.17262128]]
Progress: 16.8% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.29879469]
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[[ 0.04307745 -0.15287779  0.10103189 ..., -0.14929246  0.2158084
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  -0.24609279]
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   0.17482154]]
Progress: 16.8% ... Training loss: 0.282 ... Validation loss: 0.447[[ 0.3155214 ]
 [-0.28251853]
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[[ 0.04421658 -0.15395173  0.09820375 ..., -0.14964239  0.21940122
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   0.17454881]]
Progress: 16.8% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.30407711]
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[[ 0.04352991 -0.15329941  0.10003956 ..., -0.14945497  0.21762301
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 [ 0.04691411 -0.01472033 -0.07519516 ...,  0.04180074  0.49697725
   0.17517717]]
Progress: 16.8% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.32022295]
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[[ 0.04427324 -0.15406098  0.09823417 ..., -0.14967202  0.21968785
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   0.17457241]]
Progress: 16.8% ... Training loss: 0.275 ... Validation loss: 0.443[[ 0.29868535]
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[[ 0.04198599 -0.15205095  0.10353333 ..., -0.14909706  0.21378724
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 [ 0.04698804 -0.01479552 -0.07553463 ...,  0.04177564  0.49743801
   0.17456769]]
Progress: 16.8% ... Training loss: 0.275 ... Validation loss: 0.441[[ 0.31452007]
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[[ 0.0433442  -0.15339727  0.10012944 ..., -0.14952207  0.21735054
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 [ 0.04741813 -0.01522743 -0.07656687 ...,  0.04164403  0.49868092
   0.17352488]]
Progress: 16.8% ... Training loss: 0.263 ... Validation loss: 0.432[[ 0.29901217]
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[[ 0.04196066 -0.15213728  0.10353589 ..., -0.14916306  0.21380366
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 [ 0.04706662 -0.0149075  -0.07573066 ...,  0.04173273  0.49819511
   0.17448729]]
Progress: 16.8% ... Training loss: 0.271 ... Validation loss: 0.440[[ 0.31592534]
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[[ 0.0433357  -0.15348316  0.09994785 ..., -0.14959579  0.21767627
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 [ 0.0431946   0.04381266  0.09373468 ..., -0.24634506 -0.00224132
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 [-0.18695199 -0.1992923  -0.13996714 ...,  0.09769271 -0.09292074
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 [ 0.04811766 -0.01591357 -0.07847896 ...,  0.04141196  0.50133905
   0.1714795 ]]
Progress: 16.8% ... Training loss: 0.269 ... Validation loss: 0.437[[ 0.31130587]
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[[ 0.04285046 -0.1530804   0.10111883 ..., -0.14948042  0.21616903
  -0.1627093 ]
 [ 0.04330123  0.04371576  0.09349652 ..., -0.24637126 -0.00192889
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 [-0.18718817 -0.19909115 -0.13942265 ...,  0.09775085 -0.09350208
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  -0.24675372]
 [ 0.04846471 -0.01620909 -0.07932728 ...,  0.04132898  0.5022982
   0.17053531]]
Progress: 16.8% ... Training loss: 0.258 ... Validation loss: 0.425[[ 0.31411294]
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[[ 0.04287792 -0.1531946   0.10117393 ..., -0.14950748  0.21608895
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 [-0.18732856 -0.1989688  -0.13910506 ...,  0.09778537 -0.09400553
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  -0.24698049]
 [ 0.04864136 -0.01637469 -0.07978747 ...,  0.04127991  0.50286848
   0.17008194]]
Progress: 16.8% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.30822527]
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[[ 0.04225667 -0.15260675  0.10259361 ..., -0.14934171  0.21527018
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 [-0.18750372 -0.19880608 -0.1387536  ...,  0.09783544 -0.09459332
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   0.17066545]]
Progress: 16.8% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.30050732]
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[[ 0.04193231 -0.15224722  0.10347141 ..., -0.14923351  0.21486091
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Progress: 16.8% ... Training loss: 0.267 ... Validation loss: 0.435[[ 0.3151152 ]
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   0.17184289]]
Progress: 16.8% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.31134792]
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[[ 0.04259604 -0.15290068  0.10206293 ..., -0.14944319  0.21607212
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 [ 0.04850058 -0.01612212 -0.07960649 ...,  0.04136209  0.504504    0.1702455 ]]
Progress: 16.9% ... Training loss: 0.257 ... Validation loss: 0.424[[ 0.30239481]
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[[ 0.04297016 -0.15325225  0.10125919 ..., -0.14954803  0.2168047
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   0.16923793]]
Progress: 16.9% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.3092383 ]
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   0.1684349 ]]
Progress: 16.9% ... Training loss: 0.260 ... Validation loss: 0.419[[ 0.31028036]
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[[ 0.04335074 -0.1536407   0.10017077 ..., -0.14965603  0.21698045
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   0.1679951 ]]
Progress: 16.9% ... Training loss: 0.258 ... Validation loss: 0.423[[ 0.30253921]
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[[ 0.0428502  -0.1530759   0.10161532 ..., -0.14949134  0.21597404
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   0.16811534]]
Progress: 16.9% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.30790796]
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[[ 0.0428807  -0.15311382  0.10162223 ..., -0.14948915  0.215958
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   0.16744397]]
Progress: 16.9% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.3056616 ]
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[[ 0.04376455 -0.15394061  0.09951823 ..., -0.14974436  0.21847846
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 [ 0.0496145  -0.01710775 -0.08268065 ...,  0.0410558   0.50812987
   0.16670666]]
Progress: 16.9% ... Training loss: 0.256 ... Validation loss: 0.421[[ 0.31391315]
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[[ 0.04409261 -0.15429485  0.09865121 ..., -0.14986116  0.21933691
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   0.16723518]]
Progress: 16.9% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.30329516]
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[[ 0.04309291 -0.15332434  0.10121769 ..., -0.14957322  0.21720106
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 [ 0.04905347 -0.01658623 -0.0813893  ...,  0.04120357  0.5069643
   0.16829047]]
Progress: 16.9% ... Training loss: 0.258 ... Validation loss: 0.425[[ 0.3132349 ]
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[[ 0.04393549 -0.15412673  0.09937457 ..., -0.14983169  0.21923489
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   0.16774229]]
Progress: 16.9% ... Training loss: 0.264 ... Validation loss: 0.428[[ 0.30528504]
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[[ 0.0435127  -0.15375343  0.10040141 ..., -0.14972213  0.21817794
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   0.16838555]]
Progress: 16.9% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.30860631]
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[[ 0.04316523 -0.1533811   0.10157843 ..., -0.1496116   0.21759549
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   0.16782252]]
Progress: 16.9% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.30634599]
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[[ 0.04310327 -0.15329612  0.10181465 ..., -0.1495896   0.21736668
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   0.16745696]]
Progress: 16.9% ... Training loss: 0.256 ... Validation loss: 0.423[[ 0.30440497]
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   0.16744844]]
Progress: 16.9% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.30916096]
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 [ 0.37848587]
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[[ 0.04375775 -0.15385759  0.10064345 ..., -0.14978861  0.21965955
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   0.1673378 ]]
Progress: 16.9% ... Training loss: 0.256 ... Validation loss: 0.428[[ 0.31180717]
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[[ 0.04435672 -0.15439384  0.09911316 ..., -0.14995671  0.22168543
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  -0.2455745 ]
 [ 0.04927969 -0.0167648  -0.08223041 ...,  0.04113398  0.50869674
   0.16716005]]
Progress: 17.0% ... Training loss: 0.261 ... Validation loss: 0.432[[ 0.30765303]
 [-0.28599583]
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 [ 1.64038382]
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[[ 0.04422125 -0.15427809  0.09954805 ..., -0.14993964  0.22153931
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 [ 0.04929569 -0.0167667  -0.08225219 ...,  0.0411328   0.50893164
   0.16704786]]
Progress: 17.0% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.30251311]
 [-0.29047081]
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[[ 0.04433254 -0.15439821  0.09940095 ..., -0.14998282  0.22159895
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   0.16722692]]
Progress: 17.0% ... Training loss: 0.259 ... Validation loss: 0.424[[ 0.30980403]
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[[ 0.04447323 -0.15452293  0.09908159 ..., -0.15001793  0.22211906
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   0.16637997]]
Progress: 17.0% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.29578417]
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[[ 0.04336782 -0.15347565  0.10168252 ..., -0.14971362  0.21970044
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   0.16788512]]
Progress: 17.0% ... Training loss: 0.272 ... Validation loss: 0.435[[ 0.31188761]
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[[ 0.04433263 -0.15447555  0.09914449 ..., -0.15002732  0.22250077
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   0.16648286]]
Progress: 17.0% ... Training loss: 0.264 ... Validation loss: 0.431[[ 0.29752148]
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[[ 0.04333073 -0.15357195  0.10144064 ..., -0.14977466  0.21953923
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   0.16771625]]
Progress: 17.0% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.30235911]
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[[ 0.04408583 -0.15429533  0.09943787 ..., -0.15000486  0.22208478
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 [ 0.04879115 -0.01628028 -0.08156866 ...,  0.04126817  0.50936438
   0.16742055]]
Progress: 17.0% ... Training loss: 0.256 ... Validation loss: 0.422[[ 0.30417076]
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[[ 0.04390915 -0.15410614  0.09999711 ..., -0.14995646  0.22163355
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   0.16773405]]
Progress: 17.0% ... Training loss: 0.256 ... Validation loss: 0.422[[ 0.30782556]
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[[ 0.04433784 -0.1545566   0.09891206 ..., -0.15008245  0.2234129
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 [ 0.048454   -0.01592606 -0.08070797 ...,  0.04139042  0.50945568
   0.16825672]]
Progress: 17.0% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.30905312]
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[[ 0.04443263 -0.15463242  0.09879785 ..., -0.15010771  0.22421185
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 [-0.18443452 -0.20178042 -0.14648358 ...,  0.09690475 -0.08711976
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 [ 0.04828729 -0.01576462 -0.0804037  ...,  0.04143695  0.50950711
   0.16859317]]
Progress: 17.0% ... Training loss: 0.258 ... Validation loss: 0.425[[ 0.30545963]
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[[ 0.04373144 -0.15398263  0.10035608 ..., -0.14991251  0.22216956
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 [ 0.04822517 -0.01567572 -0.08028055 ...,  0.041469    0.50984803
   0.16874529]]
Progress: 17.0% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.30499872]
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[[ 0.04348085 -0.15372362  0.10133551 ..., -0.14983587  0.22174613
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   0.1690458 ]]
Progress: 17.0% ... Training loss: 0.257 ... Validation loss: 0.426[[ 0.30555638]
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[[ 0.04301127 -0.15328322  0.10254408 ..., -0.14969483  0.22056316
  -0.16022458]
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  -0.24432924]
 [ 0.04830207 -0.01573119 -0.08046953 ...,  0.04145197  0.51058671
   0.16844118]]
Progress: 17.0% ... Training loss: 0.257 ... Validation loss: 0.427[[ 0.30966539]
 [-0.28670124]
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 [-0.74588905]
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 [ 1.63134673]
 [ 0.37545234]
 [-0.55586359]
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[[ 0.04346072 -0.15368548  0.10145021 ..., -0.1498207   0.22198675
  -0.16143079]
 [ 0.0430563   0.04391752  0.09381728 ..., -0.24633496 -0.00163917
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 [-0.18469611 -0.20154871 -0.145754   ...,  0.09697326 -0.08788491
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  -0.24458071]
 [ 0.04835799 -0.01577626 -0.08063269 ...,  0.04143737  0.51084549
   0.16811622]]
Progress: 17.0% ... Training loss: 0.257 ... Validation loss: 0.430[[ 0.31355003]
 [-0.28333469]
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 [ 1.63622196]
 [ 0.37997902]
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[[ 0.04354223 -0.15379278  0.10146219 ..., -0.14985023  0.22201832
  -0.16146248]
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 [-0.18481513 -0.20145087 -0.14543032 ...,  0.09700428 -0.08829841
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  -0.24502317]
 [ 0.04819294 -0.01561125 -0.08022787 ...,  0.04148552  0.51058243
   0.16851783]]
Progress: 17.1% ... Training loss: 0.260 ... Validation loss: 0.435[[ 0.30475773]
 [-0.29172691]
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 [ 1.62913164]
 [ 0.37226132]
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[[ 0.0430166  -0.15323249  0.10264695 ..., -0.14970001  0.22077208
  -0.16025171]
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 [-0.18483509 -0.20142689 -0.14538592 ...,  0.09700639 -0.08850089
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  -0.24506471]
 [ 0.04788865 -0.01533043 -0.0794837  ...,  0.04156666  0.51006995
   0.16941385]]
Progress: 17.1% ... Training loss: 0.260 ... Validation loss: 0.427[[ 0.31031291]
 [-0.28768386]
 [-0.77322144]
 [-0.74746186]
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 [ 1.63218595]
 [ 0.37585983]
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[[ 0.04333373 -0.15351555  0.1018388  ..., -0.14979742  0.2219717
  -0.1612179 ]
 [ 0.04303765  0.0439201   0.09384977 ..., -0.24633087 -0.00166272
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 [-0.18438204 -0.20184364 -0.14654881 ...,  0.0968726  -0.08722635
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  -0.24484035]
 [ 0.04829954 -0.01574927 -0.08052135 ...,  0.04143688  0.51141879
   0.16821284]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.431[[ 0.30170474]
 [-0.29547333]
 [-0.78239073]
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 [ 1.62362566]
 [ 0.36779641]
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[[ 0.04220831 -0.15242963  0.10456768 ..., -0.14946588  0.2194264
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 [ 0.04310179  0.04386012  0.09369356 ..., -0.24634885 -0.00147503
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 [-0.18462318 -0.20162291 -0.14597601 ...,  0.0969379  -0.0879075
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  -0.2438461 ]
 [ 0.04793819 -0.01537288 -0.0795347  ...,  0.04155525  0.51112286
   0.16934033]]
Progress: 17.1% ... Training loss: 0.267 ... Validation loss: 0.431[[ 0.30004739]
 [-0.29606018]
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 [-0.75422984]
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 [ 0.3673331 ]
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[[ 0.04164361 -0.15181762  0.10614646 ..., -0.14927801  0.21849285
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 [ 0.04332328  0.04364436  0.09316205 ..., -0.24641493 -0.00078756
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  -0.24393076]
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   0.17086397]]
Progress: 17.1% ... Training loss: 0.272 ... Validation loss: 0.434[[ 0.3172802 ]
 [-0.27980265]
 [-0.76801935]
 [-0.73966143]
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 [ 1.63756132]
 [ 0.38326402]
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[[  4.30442603e-02  -1.53217351e-01   1.02654047e-01 ...,  -1.49722269e-01
    2.22155374e-01  -1.60565637e-01]
 [  4.33408131e-02   4.36346168e-02   9.30116265e-02 ...,  -2.46419191e-01
   -6.14524069e-04   1.08884768e-01]
 [ -1.10329825e-01   3.61642347e-02   2.37852829e-01 ...,   1.60571907e-01
   -2.73313696e-01   6.58330758e-01]
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 [ -1.84165558e-01  -2.02074850e-01  -1.47097028e-01 ...,   9.67917498e-02
   -8.66436943e-02  -7.10909398e-02]
 [ -2.78538964e-01  -2.32830929e-01  -7.08477938e-02 ...,  -1.22810236e-01
   -4.34451154e-02  -2.44515099e-01]
 [  4.80336061e-02  -1.54276263e-02  -7.97231083e-02 ...,   4.15368729e-02
    5.11779716e-01   1.69267412e-01]]
Progress: 17.1% ... Training loss: 0.272 ... Validation loss: 0.451[[ 0.30544912]
 [-0.29026894]
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 [ 1.63333228]
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[[ 0.04237909 -0.15261542  0.10430069 ..., -0.14955999  0.22047823
  -0.15910256]
 [ 0.04315231  0.04379748  0.09344681 ..., -0.24637161 -0.00117316
   0.10939299]
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 [-0.18423696 -0.2020135  -0.14693406 ...,  0.09680917 -0.08683322
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  -0.24388751]
 [ 0.04777649 -0.01515205 -0.07917618 ...,  0.04161308  0.51171614
   0.16973658]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.30847784]
 [-0.28824863]
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[[ 0.0426207  -0.15284042  0.1038633  ..., -0.14962603  0.22108499
  -0.15957393]
 [ 0.04314284  0.04381057  0.09346876 ..., -0.24637059 -0.00117921
   0.10948231]
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   0.65657062]
 ..., 
 [-0.18431402 -0.2019391  -0.14672791 ...,  0.09683817 -0.08712735
  -0.07082974]
 [-0.27886906 -0.23253028 -0.07010435 ..., -0.12273416 -0.04433525
  -0.24380121]
 [ 0.04794762 -0.01529569 -0.07954224 ...,  0.04156946  0.51228825
   0.1692959 ]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.426[[ 0.31003091]
 [-0.28732701]
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[[ 0.04319258 -0.15337702  0.1025323  ..., -0.14978764  0.22281508
  -0.16075498]
 [ 0.04318461  0.04377141  0.09336562 ..., -0.24638152 -0.00102269
   0.10940007]
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 [-0.18430481 -0.20195625 -0.14672753 ...,  0.09683316 -0.08702675
  -0.0708409 ]
 [-0.27912959 -0.23228961 -0.06952667 ..., -0.12266064 -0.04501861
  -0.24328786]
 [ 0.04744685 -0.01480652 -0.0783107  ...,  0.04171969  0.51129243
   0.17071264]]
Progress: 17.1% ... Training loss: 0.257 ... Validation loss: 0.427[[ 0.30277066]
 [-0.29395369]
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[[ 0.04293668 -0.15317029  0.10330957 ..., -0.14973195  0.22215551
  -0.16008199]
 [ 0.04325711  0.04370705  0.09319532 ..., -0.24639915 -0.00083265
   0.10921738]
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 ..., 
 [-0.18450605 -0.20178186 -0.14619998 ...,  0.09688663 -0.08753974
  -0.07039411]
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  -0.24278807]
 [ 0.04724192 -0.01461178 -0.07770206 ...,  0.04177979  0.51133104
   0.17149782]]
Progress: 17.1% ... Training loss: 0.258 ... Validation loss: 0.424[[ 0.31616977]
 [-0.28426627]
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[[ 0.04359314 -0.15379994  0.10160893 ..., -0.14993035  0.22365165
  -0.16199771]
 [ 0.04320553  0.04375866  0.09328103 ..., -0.24638472 -0.00094046
   0.10921835]
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   0.65308151]
 ..., 
 [-0.18423056 -0.2020411  -0.14685133 ...,  0.09680515 -0.08695279
  -0.07119978]
 [-0.27944001 -0.23200031 -0.06877407 ..., -0.12257175 -0.04590826
  -0.24240834]
 [ 0.04774769 -0.01511932 -0.07908644 ...,  0.04162108  0.51267966
   0.17002938]]
Progress: 17.1% ... Training loss: 0.268 ... Validation loss: 0.440[[ 0.30317266]
 [-0.29460647]
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 [ 1.63519257]
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[[ 0.04257351 -0.15285151  0.10405611 ..., -0.14965998  0.22212306
  -0.15910927]
 [ 0.04320553  0.04375866  0.09328103 ..., -0.24638472 -0.00094046
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 [-0.18454562 -0.20177147 -0.14610831 ...,  0.09688745 -0.0877621
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  -0.24222127]
 [ 0.04677183 -0.01420646 -0.07672567 ...,  0.04188584  0.51124881
   0.17257916]]
Progress: 17.1% ... Training loss: 0.259 ... Validation loss: 0.422[[ 0.30456015]
 [-0.29243534]
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[[  4.23455336e-02  -1.52630055e-01   1.04525867e-01 ...,  -1.49579900e-01
    2.21379075e-01  -1.58686169e-01]
 [  4.34864665e-02   4.34876311e-02   9.25739492e-02 ...,  -2.46463967e-01
   -8.83641043e-05   1.08535035e-01]
 [ -1.08092426e-01   3.37354850e-02   2.33037597e-01 ...,   1.59911597e-01
   -2.69071306e-01   6.53806758e-01]
 ..., 
 [ -1.84543517e-01  -2.01770809e-01  -1.46099484e-01 ...,   9.68875864e-02
   -8.77732053e-02  -7.02503419e-02]
 [ -2.79314998e-01  -2.32120423e-01  -6.90883449e-02 ...,  -1.22606603e-01
   -4.57148714e-02  -2.42652397e-01]
 [  4.70349210e-02  -1.44585198e-02  -7.73616185e-02 ...,   4.18088794e-02
    5.11978823e-01   1.71821119e-01]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.421[[ 0.30421277]
 [-0.29167609]
 [-0.77682657]
 [-0.75064239]
 [-0.20192981]
 [ 1.63495979]
 [ 0.37265613]
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 [ 2.15233231]
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 [ 0.58862631]
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 [ 0.93015776]
 [-0.87419269]]
[[  4.26445983e-02  -1.52854616e-01   1.04036093e-01 ...,  -1.49658654e-01
    2.22125684e-01  -1.59290699e-01]
 [  4.34628090e-02   4.35145501e-02   9.25975260e-02 ...,  -2.46455843e-01
   -1.13126393e-04   1.08552599e-01]
 [ -1.08301580e-01   3.39798396e-02   2.33682270e-01 ...,   1.59967295e-01
   -2.69309765e-01   6.54482307e-01]
 ..., 
 [ -1.84432267e-01  -2.01869106e-01  -1.46301464e-01 ...,   9.68608059e-02
   -8.75211896e-02  -7.04936754e-02]
 [ -2.79424186e-01  -2.32006740e-01  -6.89299538e-02 ...,  -1.22578598e-01
   -4.59731126e-02  -2.42467731e-01]
 [  4.70892509e-02  -1.45026818e-02  -7.74042370e-02 ...,   4.17983847e-02
    5.12151062e-01   1.71717122e-01]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.422[[ 0.30514391]
 [-0.28993394]
 [-0.77559004]
 [-0.75077149]
 [-0.20259645]
 [ 1.63810496]
 [ 0.37507288]
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[[  4.28343437e-02  -1.53000813e-01   1.03683518e-01 ...,  -1.49702337e-01
    2.23058236e-01  -1.60012006e-01]
 [  4.34978300e-02   4.34813175e-02   9.25085582e-02 ...,  -2.46466362e-01
    6.46455426e-06   1.08454264e-01]
 [ -1.07307398e-01   3.30213012e-02   2.31272115e-01 ...,   1.59677861e-01
   -2.66971962e-01   6.51975773e-01]
 ..., 
 [ -1.84565121e-01  -2.01739004e-01  -1.46008662e-01 ...,   9.68987029e-02
   -8.78850822e-02  -7.02818031e-02]
 [ -2.79167749e-01  -2.32252427e-01  -6.95499057e-02 ...,  -1.22647064e-01
   -4.54084125e-02  -2.43233324e-01]
 [  4.68976016e-02  -1.43064016e-02  -7.68675636e-02 ...,   4.18620875e-02
    5.12159101e-01   1.72040856e-01]]
Progress: 17.1% ... Training loss: 0.256 ... Validation loss: 0.421[[ 0.30695527]
 [-0.2893181 ]
 [-0.77442473]
 [-0.75012141]
 [-0.20142442]
 [ 1.64377366]
 [ 0.3785376 ]
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 [ 2.15936088]
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 [ 0.93535271]
 [-0.86917596]]
[[  4.32057706e-02  -1.53319401e-01   1.02814797e-01 ...,  -1.49821754e-01
    2.24153117e-01  -1.61052228e-01]
 [  4.34411535e-02   4.35368876e-02   9.26562190e-02 ...,  -2.46450796e-01
   -1.05956760e-04   1.08623860e-01]
 [ -1.06666484e-01   3.24243027e-02   2.29762970e-01 ...,   1.59486066e-01
   -2.65841079e-01   6.50440135e-01]
 ..., 
 [ -1.84571008e-01  -2.01724391e-01  -1.46021729e-01 ...,   9.68931517e-02
   -8.79345273e-02  -7.04761629e-02]
 [ -2.78872260e-01  -2.32517533e-01  -7.02632254e-02 ...,  -1.22731526e-01
   -4.46370516e-02  -2.43969979e-01]
 [  4.69087968e-02  -1.43036803e-02  -7.69292120e-02 ...,   4.18618139e-02
    5.12605252e-01   1.71975306e-01]]
Progress: 17.2% ... Training loss: 0.258 ... Validation loss: 0.422[[ 0.29853383]
 [-0.29674664]
 [-0.78186618]
 [-0.75873207]
 [-0.20853135]
 [ 1.63478669]
 [ 0.37075051]
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[[  4.23028457e-02  -1.52389705e-01   1.05178039e-01 ...,  -1.49547983e-01
    2.21891901e-01  -1.58773850e-01]
 [  4.35560548e-02   4.34274955e-02   9.24054577e-02 ...,  -2.46482345e-01
    2.11742166e-04   1.08403452e-01]
 [ -1.07937875e-01   3.35678195e-02   2.32867553e-01 ...,   1.59807180e-01
   -2.70179792e-01   6.54184457e-01]
 ..., 
 [ -1.84739481e-01  -2.01563435e-01  -1.45587464e-01 ...,   9.69344791e-02
   -8.84276282e-02  -7.00188136e-02]
 [ -2.78629771e-01  -2.32736006e-01  -7.08648047e-02 ...,  -1.22796996e-01
   -4.41227580e-02  -2.44563638e-01]
 [  4.64601504e-02  -1.38317624e-02  -7.58803255e-02 ...,   4.19913341e-02
    5.12047920e-01   1.72917991e-01]]
Progress: 17.2% ... Training loss: 0.264 ... Validation loss: 0.426[[ 0.31477029]
 [-0.28314054]
 [-0.77121414]
 [-0.74529661]
 [-0.19587769]
 [ 1.64239936]
 [ 0.38324248]
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 [ 0.94566103]
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[[  4.36209238e-02  -1.53702155e-01   1.01944390e-01 ...,  -1.49941773e-01
    2.25528344e-01  -1.61888246e-01]
 [  4.35491028e-02   4.34342025e-02   9.24230785e-02 ...,  -2.46480031e-01
    1.75706917e-04   1.08451009e-01]
 [ -1.07808846e-01   3.34518676e-02   2.32260926e-01 ...,   1.59766706e-01
   -2.69785005e-01   6.53724356e-01]
 ..., 
 [ -1.84424977e-01  -2.01868026e-01  -1.46332534e-01 ...,   9.68325953e-02
   -8.76142348e-02  -7.06931925e-02]
 [ -2.78508666e-01  -2.32844743e-01  -7.11684377e-02 ...,  -1.22836876e-01
   -4.38342289e-02  -2.44839506e-01]
 [  4.64607297e-02  -1.38083053e-02  -7.59441777e-02 ...,   4.19980582e-02
    5.12206895e-01   1.72801270e-01]]
Progress: 17.2% ... Training loss: 0.268 ... Validation loss: 0.444[[ 0.30404226]
 [-0.29284863]
 [-0.77897751]
 [-0.75593826]
 [-0.20708793]
 [ 1.63178984]
 [ 0.37258994]
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[[  4.30903557e-02  -1.53238124e-01   1.03231153e-01 ...,  -1.49816253e-01
    2.23773523e-01  -1.60406022e-01]
 [  4.37142911e-02   4.32889431e-02   9.20345692e-02 ...,  -2.46522537e-01
    6.19356702e-04   1.08025018e-01]
 [ -1.08561314e-01   3.41128734e-02   2.34347216e-01 ...,   1.59961694e-01
   -2.72029357e-01   6.56183809e-01]
 ..., 
 [ -1.84495704e-01  -2.01818220e-01  -1.46136268e-01 ...,   9.68486085e-02
   -8.79449954e-02  -7.04459872e-02]
 [ -2.78802767e-01  -2.32568831e-01  -7.05038298e-02 ...,  -1.22761728e-01
   -4.47172731e-02  -2.44132319e-01]
 [  4.61199178e-02  -1.34893065e-02  -7.52120002e-02 ...,   4.20875236e-02
    5.11475709e-01   1.73551645e-01]]
Progress: 17.2% ... Training loss: 0.257 ... Validation loss: 0.425[[ 0.30974849]
 [-0.28717115]
 [-0.77556997]
 [-0.75036573]
 [-0.20125934]
 [ 1.63384748]
 [ 0.37792151]
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 [ 0.18199198]
 [ 0.29133724]
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 [ 1.00573616]
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 [ 0.19112554]
 [ 0.035193  ]
 [ 2.1565285 ]
 [-0.70132676]
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[[ 0.04338516 -0.15350074  0.10274202 ..., -0.14988666  0.22426762
  -0.16105642]
 [ 0.04373897  0.04326512  0.09197092 ..., -0.24652989  0.0006705
   0.10795567]
 [-0.1089611   0.03456994  0.2352402  ...,  0.16007753 -0.27271509
   0.65660884]
 ..., 
 [-0.18427302 -0.20203456 -0.14663747 ...,  0.09678495 -0.08732137
  -0.07096786]
 [-0.27838597 -0.23298786 -0.07146966 ..., -0.12288363 -0.04391172
  -0.24500991]
 [ 0.04641391 -0.01376478 -0.07595096 ...,  0.04200542  0.51222969
   0.17270205]]
Progress: 17.2% ... Training loss: 0.257 ... Validation loss: 0.431[[ 0.30184365]
 [-0.29439412]
 [-0.78166224]
 [-0.75538334]
 [-0.204243  ]
 [ 1.62815452]
 [ 0.37292729]
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 [ 0.93329328]
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[[  4.28345887e-02  -1.52972408e-01   1.04182341e-01 ...,  -1.49725143e-01
    2.23414784e-01  -1.59227144e-01]
 [  4.37168553e-02   4.32861916e-02   9.20799891e-02 ...,  -2.46524313e-01
    6.47063827e-04   1.08128666e-01]
 [ -1.10012085e-01   3.55352774e-02   2.37931641e-01 ...,   1.60371151e-01
   -2.75515719e-01   6.59694626e-01]
 ..., 
 [ -1.84403196e-01  -2.01916488e-01  -1.46311950e-01 ...,   9.68267706e-02
   -8.78725097e-02  -7.06659999e-02]
 [ -2.78201034e-01  -2.33165433e-01  -7.19255811e-02 ...,  -1.22940984e-01
   -4.33168276e-02  -2.45339594e-01]
 [  4.59689738e-02  -1.32911756e-02  -7.48323030e-02 ...,   4.21447086e-02
    5.12056981e-01   1.73963781e-01]]
Progress: 17.2% ... Training loss: 0.259 ... Validation loss: 0.426[[ 0.31206409]
 [-0.28487265]
 [-0.77438665]
 [-0.74524585]
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 [ 1.63543943]
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[[  4.31048777e-02  -1.53265534e-01   1.03458116e-01 ...,  -1.49792687e-01
    2.24177369e-01  -1.60024121e-01]
 [  4.36921865e-02   4.33084398e-02   9.21378190e-02 ...,  -2.46516618e-01
    5.69565420e-04   1.08175648e-01]
 [ -1.09577476e-01   3.51031381e-02   2.36787714e-01 ...,   1.60238932e-01
   -2.73981181e-01   6.58360601e-01]
 ..., 
 [ -1.84281607e-01  -2.02037551e-01  -1.46594159e-01 ...,   9.67984072e-02
   -8.76468112e-02  -7.09634659e-02]
 [ -2.78006439e-01  -2.33348820e-01  -7.24713093e-02 ...,  -1.22993286e-01
   -4.28367033e-02  -2.45917093e-01]
 [  4.59750182e-02  -1.32796672e-02  -7.48511519e-02 ...,   4.21509018e-02
    5.12225176e-01   1.73892197e-01]]
Progress: 17.2% ... Training loss: 0.260 ... Validation loss: 0.437[[ 0.30317667]
 [-0.29383064]
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 [-0.75357758]
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 [ 1.6300526 ]
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 [-0.87812979]]
[[  4.24497136e-02  -1.52631211e-01   1.05124651e-01 ...,  -1.49620500e-01
    2.22307167e-01  -1.58072423e-01]
 [  4.35769429e-02   4.34199583e-02   9.23559279e-02 ...,  -2.46481622e-01
    3.22469500e-04   1.08339568e-01]
 [ -1.09636295e-01   3.51044060e-02   2.37157732e-01 ...,   1.60236177e-01
   -2.74704174e-01   6.59096637e-01]
 ..., 
 [ -1.84593397e-01  -2.01741363e-01  -1.45877686e-01 ...,   9.68798262e-02
   -8.85551357e-02  -7.01824263e-02]
 [ -2.78112920e-01  -2.33254295e-01  -7.21883840e-02 ...,  -1.22968102e-01
   -4.31377522e-02  -2.45621940e-01]
 [  4.58145312e-02  -1.31021863e-02  -7.45525988e-02 ...,   4.21968299e-02
    5.12188720e-01   1.74326769e-01]]
Progress: 17.2% ... Training loss: 0.258 ... Validation loss: 0.425[[ 0.30558512]
 [-0.29150624]
 [-0.77881682]
 [-0.75307233]
 [-0.20330948]
 [ 1.63037427]
 [ 0.37660969]
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 [ 0.18766225]
 [ 0.03182106]
 [ 2.15535388]
 [-0.70408991]
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 [ 0.59104032]
 [-0.09064272]
 [ 0.9394321 ]
 [-0.87566403]]
[[  4.26421697e-02  -1.52783500e-01   1.04798344e-01 ...,  -1.49673916e-01
    2.22848677e-01  -1.58180951e-01]
 [  4.36373466e-02   4.33609331e-02   9.22166882e-02 ...,  -2.46500244e-01
    5.08255619e-04   1.08173509e-01]
 [ -1.09884567e-01   3.53842083e-02   2.37862270e-01 ...,   1.60311123e-01
   -2.74885236e-01   6.59834749e-01]
 ..., 
 [ -1.84553375e-01  -2.01789139e-01  -1.45910280e-01 ...,   9.68682728e-02
   -8.85106643e-02  -7.01818933e-02]
 [ -2.78152094e-01  -2.33215909e-01  -7.20956493e-02 ...,  -1.22956749e-01
   -4.32401429e-02  -2.45512154e-01]
 [  4.58984414e-02  -1.31623303e-02  -7.46930454e-02 ...,   4.21803208e-02
    5.12611495e-01   1.74280547e-01]]
Progress: 17.2% ... Training loss: 0.256 ... Validation loss: 0.428[[ 0.30578468]
 [-0.29148894]
 [-0.78105423]
 [-0.75328793]
 [-0.20460092]
 [ 1.62602065]
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 [ 0.0315284 ]
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 [ 0.58904537]
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 [ 0.94227455]
 [-0.87661369]]
[[ 0.04233766 -0.15249144  0.10556351 ..., -0.14958184  0.22190656
  -0.15718493]
 [ 0.04375447  0.04325117  0.09194892 ..., -0.24653305  0.00086244
   0.10784781]
 [-0.11082502  0.03625364  0.24005967 ...,  0.16057836 -0.27758271
   0.66220791]
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 [-0.1846325  -0.20171532 -0.14572935 ...,  0.09688679 -0.08866946
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   0.17344385]]
Progress: 17.2% ... Training loss: 0.257 ... Validation loss: 0.430[[ 0.30387694]
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[[ 0.04234541 -0.15245414  0.1057683  ..., -0.14958196  0.22199856
  -0.15720374]
 [ 0.04388613  0.04312989  0.09162824 ..., -0.2465725   0.00124076
   0.10748084]
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  -0.24489785]
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   0.17395303]]
Progress: 17.2% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.30354487]
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[[ 0.0427321  -0.15283029  0.10507529 ..., -0.14969818  0.22287464
  -0.15737377]
 [ 0.04388282  0.04313272  0.09163702 ..., -0.24657182  0.00123211
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  -0.24528689]
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   0.1738183 ]]
Progress: 17.2% ... Training loss: 0.258 ... Validation loss: 0.429[[ 0.30536599]
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[[  4.26832797e-02  -1.52756025e-01   1.05331038e-01 ...,  -1.49679458e-01
    2.23100242e-01  -1.56980530e-01]
 [  4.35721413e-02   4.34420992e-02   9.23469734e-02 ...,  -2.46482007e-01
    5.41367227e-04   1.08250161e-01]
 [ -1.10178127e-01   3.54973425e-02   2.39000223e-01 ...,   1.60320881e-01
   -2.76536018e-01   6.60465995e-01]
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 [ -1.84261802e-01  -2.02058794e-01  -1.46527479e-01 ...,   9.67751853e-02
   -8.76552572e-02  -7.07949989e-02]
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   -4.25416338e-02  -2.46090321e-01]
 [  4.61237224e-02  -1.32763155e-02  -7.55249205e-02 ...,   4.21435210e-02
    5.14287690e-01   1.73527178e-01]]
Progress: 17.2% ... Training loss: 0.255 ... Validation loss: 0.429[[ 0.29904621]
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[[  4.22685310e-02  -1.52340385e-01   1.06586463e-01 ...,  -1.49559286e-01
    2.22496876e-01  -1.55806348e-01]
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    6.54136450e-04   1.08138056e-01]
 [ -1.10496071e-01   3.57460572e-02   2.39905626e-01 ...,   1.60395732e-01
   -2.77257914e-01   6.61242617e-01]
 ..., 
 [ -1.84624990e-01  -2.01723332e-01  -1.45616821e-01 ...,   9.68799446e-02
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 [ -2.78059634e-01  -2.33319794e-01  -7.22157586e-02 ...,  -1.22982858e-01
   -4.31984335e-02  -2.45495986e-01]
 [  4.62900075e-02  -1.34205941e-02  -7.58866285e-02 ...,   4.20979505e-02
    5.14908114e-01   1.73087250e-01]]
Progress: 17.2% ... Training loss: 0.261 ... Validation loss: 0.426[[ 0.30830568]
 [-0.28747464]
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 [ 1.63008825]
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[[ 0.04291264 -0.15296376  0.10498353 ..., -0.14975704  0.22463028
  -0.15782363]
 [ 0.04360536  0.04341114  0.09230265 ..., -0.24649445  0.00074311
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 [-0.18414197 -0.20220585 -0.14675347 ...,  0.09673666 -0.08760885
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 [ 0.04631191 -0.01343475 -0.07594928 ...,  0.04209603  0.51530824
   0.1729081 ]]
Progress: 17.2% ... Training loss: 0.257 ... Validation loss: 0.438[[ 0.29332616]
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[[ 0.04231361 -0.15235491  0.10638206 ..., -0.14957525  0.22277778
  -0.1563157 ]
 [ 0.04369278  0.0433315   0.09207903 ..., -0.24651956  0.00106069
   0.10794748]
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 [-0.18463573 -0.20175181 -0.14557123 ...,  0.09687468 -0.0890676
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 [ 0.04601468 -0.01314125 -0.07517987 ...,  0.04216911  0.51470044
   0.17369686]]
Progress: 17.3% ... Training loss: 0.275 ... Validation loss: 0.434[[ 0.32021356]
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[[ 0.04441463 -0.15451528  0.10106015 ..., -0.15026436  0.22823799
  -0.16149799]
 [ 0.04373575  0.04329336  0.0919352  ..., -0.24652983  0.00123452
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 [-0.18393614 -0.20245368 -0.1473565  ...,  0.09664534 -0.08712529
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  -0.24646394]
 [ 0.04620287 -0.01333801 -0.07568175 ...,  0.04210623  0.5151565
   0.17306732]]
Progress: 17.3% ... Training loss: 0.304 ... Validation loss: 0.509[[ 0.2877743 ]
 [-0.30223543]
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[[ 0.04187653 -0.15229251  0.10708247 ..., -0.14967288  0.2217484
  -0.15545172]
 [ 0.04353777  0.04346472  0.09229154 ..., -0.24648385  0.00079278
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 [-0.18389276 -0.20250116 -0.14740571 ...,  0.09663354 -0.08711771
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  -0.24501602]
 [ 0.04523068 -0.0124523  -0.07334758 ...,  0.04234282  0.51331693
   0.17532823]]
Progress: 17.3% ... Training loss: 0.293 ... Validation loss: 0.446[[ 0.31271472]
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[[ 0.04334666 -0.15386823  0.103121   ..., -0.15017723  0.22573678
  -0.15963131]
 [ 0.04350425  0.0434989   0.09238385 ..., -0.24647248  0.00068687
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 [-0.18328216 -0.20315469 -0.14909656 ...,  0.09642475 -0.08561823
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  -0.24630119]
 [ 0.04606728 -0.01334177 -0.0755949  ...,  0.04205031  0.51560286
   0.17300745]]
Progress: 17.3% ... Training loss: 0.274 ... Validation loss: 0.460[[ 0.30077888]
 [-0.28963198]
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[[  4.22784951e-02  -1.52894432e-01   1.05966256e-01 ...,  -1.49910951e-01
    2.22698221e-01  -1.55980145e-01]
 [  4.33928659e-02   4.36037306e-02   9.25655794e-02 ...,  -2.46443138e-01
    5.14951496e-04   1.08301166e-01]
 [ -1.10837437e-01   3.57278621e-02   2.41273147e-01 ...,   1.60279283e-01
   -2.78611278e-01   6.62987447e-01]
 ..., 
 [ -1.83428141e-01  -2.03019799e-01  -1.48744200e-01 ...,   9.64582879e-02
   -8.60068809e-02  -7.29504845e-02]
 [ -2.77978145e-01  -2.33562744e-01  -7.26671958e-02 ...,  -1.23108421e-01
   -4.31182176e-02  -2.45757355e-01]
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    5.14153564e-01   1.74709087e-01]]
Progress: 17.3% ... Training loss: 0.256 ... Validation loss: 0.429[[ 0.30289184]
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[[ 0.04216211 -0.15279272  0.10632629 ..., -0.14986903  0.22218912
  -0.15567422]
 [ 0.04349868  0.04350224  0.09229749 ..., -0.24647389  0.00083357
   0.10805803]
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 [-0.18355138 -0.20290429 -0.14838017 ...,  0.09649173 -0.08643509
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  -0.24566404]
 [ 0.04554408 -0.01288719 -0.07432794 ...,  0.04218169  0.51442904
   0.17438558]]
Progress: 17.3% ... Training loss: 0.256 ... Validation loss: 0.432[[ 0.30719233]
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[[  4.24067685e-02  -1.53031706e-01   1.05738872e-01 ...,  -1.49957867e-01
    2.22582235e-01  -1.56230502e-01]
 [  4.34215538e-02   4.35754882e-02   9.25022053e-02 ...,  -2.46451590e-01
    5.90799753e-04   1.08276370e-01]
 [ -1.11268562e-01   3.61781091e-02   2.42707926e-01 ...,   1.60405751e-01
   -2.79724621e-01   6.64070991e-01]
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 [ -1.83640682e-01  -2.02820661e-01  -1.48165942e-01 ...,   9.65181049e-02
   -8.67418073e-02  -7.24395104e-02]
 [ -2.78019667e-01  -2.33526031e-01  -7.25512207e-02 ...,  -1.23098765e-01
   -4.34828656e-02  -2.45559945e-01]
 [  4.56613044e-02  -1.29822993e-02  -7.46679942e-02 ...,   4.21483261e-02
    5.14778992e-01   1.73952132e-01]]
Progress: 17.3% ... Training loss: 0.259 ... Validation loss: 0.441[[ 0.30544441]
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[[ 0.04256828 -0.15317822  0.10529163 ..., -0.14999447  0.22341605
  -0.15691323]
 [ 0.0435092   0.04349553  0.09227892 ..., -0.24647436  0.00085202
   0.10805414]
 [-0.11079672  0.03563313  0.24171797 ...,  0.16024973 -0.27898273
   0.66315335]
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 [-0.18368965 -0.20277865 -0.14802632 ...,  0.0965269  -0.08689161
  -0.07228345]
 [-0.27815147 -0.23340901 -0.07229226 ..., -0.12306263 -0.04387206
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 [ 0.04561064 -0.01291845 -0.07456244 ...,  0.04216496  0.51512837
   0.17401462]]
Progress: 17.3% ... Training loss: 0.258 ... Validation loss: 0.436[[ 0.29560176]
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[[  4.17541107e-02  -1.52375724e-01   1.07221933e-01 ...,  -1.49770158e-01
    2.21382467e-01  -1.54640705e-01]
 [  4.33994620e-02   4.35995685e-02   9.24579612e-02 ...,  -2.46442463e-01
    5.74895388e-04   1.08209266e-01]
 [ -1.11264238e-01   3.59862671e-02   2.43019286e-01 ...,   1.60350401e-01
   -2.80572455e-01   6.65221697e-01]
 ..., 
 [ -1.84237681e-01  -2.02273685e-01  -1.46699966e-01 ...,   9.66791751e-02
   -8.85633680e-02  -7.08530803e-02]
 [ -2.78523889e-01  -2.33067907e-01  -7.13653470e-02 ...,  -1.22962292e-01
   -4.49373549e-02  -2.44242932e-01]
 [  4.56219741e-02  -1.29162514e-02  -7.45914080e-02 ...,   4.21607286e-02
    5.15364225e-01   1.73909447e-01]]
Progress: 17.3% ... Training loss: 0.262 ... Validation loss: 0.429[[ 0.30955158]
 [-0.28165872]
 [-0.77480046]
 [-0.74197751]
 [-0.19455421]
 [ 1.6359161 ]
 [ 0.38251507]
 [-0.55850422]
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 [ 0.73998225]
 [ 0.17840325]
 [ 0.29461147]
 [-0.03812468]
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 [ 0.37372155]
 [ 1.00481019]
 [-0.46605667]
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 [ 0.19809161]
 [ 0.04485565]
 [ 2.16252885]
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 [-0.98675962]
 [ 0.5947624 ]
 [-0.08243581]
 [ 0.95341502]
 [-0.87061804]]
[[  4.24739414e-02  -1.53095939e-01   1.05457303e-01 ...,  -1.49991611e-01
    2.23482930e-01  -1.56569335e-01]
 [  4.34030822e-02   4.35981597e-02   9.24569735e-02 ...,  -2.46445238e-01
    6.30364968e-04   1.08211476e-01]
 [ -1.10451847e-01   3.51640110e-02   2.40792635e-01 ...,   1.60084207e-01
   -2.77970144e-01   6.62689379e-01]
 ..., 
 [ -1.83781321e-01  -2.02713763e-01  -1.47834571e-01 ...,   9.65322956e-02
   -8.72325939e-02  -7.20230255e-02]
 [ -2.78410065e-01  -2.33179025e-01  -7.16103877e-02 ...,  -1.22997347e-01
   -4.45663181e-02  -2.44398357e-01]
 [  4.61925635e-02  -1.35037215e-02  -7.61229654e-02 ...,   4.19754156e-02
    5.17079767e-01   1.72460624e-01]]
Progress: 17.3% ... Training loss: 0.266 ... Validation loss: 0.447[[ 0.29488217]
 [-0.29455277]
 [-0.78802003]
 [-0.75607338]
 [-0.20693514]
 [ 1.62538544]
 [ 0.36905006]
 [-0.57293892]
 [-0.43216693]
 [ 0.72609405]
 [ 0.1651402 ]
 [ 0.28142423]
 [-0.05243485]
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 [ 0.99059191]
 [-0.48029393]
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 [ 0.03114156]
 [ 2.15337581]
 [-0.71099812]
 [-1.00177057]
 [ 0.58252965]
 [-0.09594987]
 [ 0.93644303]
 [-0.88285366]]
[[ 0.04156693 -0.15229299  0.10776289 ..., -0.14975915  0.22128612
  -0.15399204]
 [ 0.04349455  0.04351509  0.09223939 ..., -0.24646852  0.00088228
   0.1079739 ]
 [-0.11122379  0.035869    0.24294473 ...,  0.1602907  -0.28015711
   0.66488499]
 ..., 
 [-0.18445349 -0.20210444 -0.14621541 ...,  0.09670958 -0.08917975
  -0.070339  ]
 [-0.27880351 -0.23282828 -0.0707359  ..., -0.12289759 -0.04573113
  -0.24353034]
 [ 0.04597328 -0.01328299 -0.07569404 ...,  0.04203298  0.51693361
   0.17295607]]
Progress: 17.3% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.30427307]
 [-0.28669595]
 [-0.78090618]
 [-0.74635954]
 [-0.19859712]
 [ 1.63306045]
 [ 0.37797312]
 [-0.56424767]
 [-0.42482721]
 [ 0.73315142]
 [ 0.17397156]
 [ 0.28912055]
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 [ 0.36795091]
 [ 0.99876081]
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 [ 0.19347751]
 [ 0.04013778]
 [ 2.15978753]
 [-0.70178507]
 [-0.99290646]
 [ 0.59077962]
 [-0.08768437]
 [ 0.94775515]
 [-0.87626855]]
[[ 0.04232964 -0.15303929  0.10588383 ..., -0.14999953  0.22326974
  -0.15552697]
 [ 0.04348323  0.04353848  0.09228955 ..., -0.24646831  0.00088266
   0.10810036]
 [-0.11088899  0.03553054  0.24208841 ...,  0.16017181 -0.27905453
   0.66398071]
 ..., 
 [-0.1843348  -0.20221711 -0.14649508 ...,  0.09666855 -0.08898311
  -0.07064603]
 [-0.27862512 -0.23301522 -0.07116793 ..., -0.12295332 -0.04541904
  -0.24382254]
 [ 0.04605867 -0.01334991 -0.0759099  ...,  0.0420219   0.5176101
   0.17275779]]
Progress: 17.3% ... Training loss: 0.256 ... Validation loss: 0.431[[ 0.29594084]
 [-0.29589713]
 [-0.78933721]
 [-0.75335159]
 [-0.20660982]
 [ 1.62480258]
 [ 0.36905497]
 [-0.57113187]
 [-0.43328093]
 [ 0.72384965]
 [ 0.166854  ]
 [ 0.28102387]
 [-0.05312789]
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 [ 0.35933282]
 [ 0.99017924]
 [-0.47938915]
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 [ 0.18472126]
 [ 0.03165366]
 [ 2.15271241]
 [-0.70831067]
 [-1.00078485]
 [ 0.58215258]
 [-0.09626836]
 [ 0.93793328]
 [-0.88421331]]
[[  4.17769430e-02  -1.52549297e-01   1.07240290e-01 ...,  -1.49865294e-01
    2.21926833e-01  -1.54027275e-01]
 [  4.31804474e-02   4.38173784e-02   9.30373144e-02 ...,  -2.46393165e-01
    1.89081495e-04   1.08948999e-01]
 [ -1.11943817e-01   3.65120146e-02   2.44735334e-01 ...,   1.60455211e-01
   -2.81528969e-01   6.66892707e-01]
 ..., 
 [ -1.84442817e-01  -2.02115922e-01  -1.46234918e-01 ...,   9.66996781e-02
   -8.92618557e-02  -7.03073302e-02]
 [ -2.78866347e-01  -2.32791984e-01  -7.06046096e-02 ...,  -1.22891480e-01
   -4.60506840e-02  -2.43221584e-01]
 [  4.59223394e-02  -1.32227250e-02  -7.55220703e-02 ...,   4.20620554e-02
    5.17489070e-01   1.73083054e-01]]
Progress: 17.3% ... Training loss: 0.265 ... Validation loss: 0.429[[ 0.30641308]
 [-0.28575875]
 [-0.77907147]
 [-0.74286048]
 [-0.1965747 ]
 [ 1.63232963]
 [ 0.37893331]
 [-0.56205132]
 [-0.42342536]
 [ 0.73322979]
 [ 0.17626476]
 [ 0.29013222]
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 [ 0.3700402 ]
 [ 0.99843572]
 [-0.46823676]
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 [ 0.19349524]
 [ 0.04072867]
 [ 2.15857923]
 [-0.69868962]
 [-0.99000741]
 [ 0.59103376]
 [-0.08667136]
 [ 0.95020201]
 [-0.87478136]]
[[ 0.04235896 -0.15314893  0.10586079 ..., -0.15004309  0.22347714
  -0.155224  ]
 [ 0.04344095  0.04356133  0.09234029 ..., -0.24647458  0.00092399
   0.10828242]
 [-0.11101861  0.0355316   0.24247517 ...,  0.16015848 -0.27931222
   0.6645529 ]
 ..., 
 [-0.18449066 -0.20206718 -0.14611569 ...,  0.09671168 -0.08943715
  -0.07007701]
 [-0.27876486 -0.23289596 -0.07086326 ..., -0.12292485 -0.04572992
  -0.24340666]
 [ 0.04614477 -0.01343349 -0.07616174 ...,  0.04199286  0.51820484
   0.17230421]]
Progress: 17.3% ... Training loss: 0.258 ... Validation loss: 0.434[[ 0.29240547]
 [-0.29687962]
 [-0.78935066]
 [-0.75612207]
 [-0.20885263]
 [ 1.62469627]
 [ 0.3673142 ]
 [-0.57535549]
 [-0.43230597]
 [ 0.72262024]
 [ 0.16336775]
 [ 0.2773613 ]
 [-0.0558858 ]
 [-0.68756808]
 [ 0.35838621]
 [ 0.98557367]
 [-0.48162562]
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 [-0.37512467]
 [ 0.18280995]
 [ 0.02937841]
 [ 2.15198549]
 [-0.71052457]
 [-1.00426315]
 [ 0.58113279]
 [-0.0982308 ]
 [ 0.93453854]
 [-0.88210254]]
[[ 0.0412922  -0.15213696  0.10865156 ..., -0.1497415   0.2206692
  -0.15287401]
 [ 0.04342322  0.04357832  0.09237764 ..., -0.24646952  0.00088383
   0.10833745]
 [-0.11050878  0.03497794  0.2415886  ...,  0.15999538 -0.27901182
   0.66422082]
 ..., 
 [-0.18502274 -0.20157878 -0.14483373 ...,  0.09685606 -0.09100031
  -0.06865615]
 [-0.2790831  -0.23260595 -0.07007782 ..., -0.12283795 -0.04667795
  -0.24260858]
 [ 0.04565288 -0.01292739 -0.07514673 ...,  0.04214278  0.51739674
   0.17327015]]
Progress: 17.3% ... Training loss: 0.269 ... Validation loss: 0.433[[ 0.30685383]
 [-0.28392691]
 [-0.78096736]
 [-0.74156483]
 [-0.19661111]
 [ 1.62844151]
 [ 0.37817415]
 [-0.56153095]
 [-0.42392014]
 [ 0.73264671]
 [ 0.17484817]
 [ 0.28873821]
 [-0.04309357]
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 [ 0.37027135]
 [ 0.99722836]
 [-0.46846065]
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 [ 0.19611005]
 [ 0.0417911 ]
 [ 2.15604398]
 [-0.69738584]
 [-0.98799136]
 [ 0.58835105]
 [-0.08661266]
 [ 0.95180754]
 [-0.87546385]]
[[  4.19004702e-02  -1.52813649e-01   1.07334326e-01 ...,  -1.49954611e-01
    2.21703390e-01  -1.53621233e-01]
 [  4.31784965e-02   4.38343675e-02   9.29569513e-02 ...,  -2.46390079e-01
    3.35503532e-04   1.08989752e-01]
 [ -1.11917298e-01   3.64565971e-02   2.45017020e-01 ...,   1.60465768e-01
   -2.82607383e-01   6.67031551e-01]
 ..., 
 [ -1.84957032e-01  -2.01650966e-01  -1.45002983e-01 ...,   9.68337371e-02
   -9.08220999e-02  -6.88712268e-02]
 [ -2.78950566e-01  -2.32755996e-01  -7.03467156e-02 ...,  -1.22880285e-01
   -4.64438622e-02  -2.42632379e-01]
 [  4.65671007e-02  -1.38575285e-02  -7.75426325e-02 ...,   4.18393399e-02
    5.19622532e-01   1.70874551e-01]]
Progress: 17.4% ... Training loss: 0.258 ... Validation loss: 0.437[[ 0.3001514 ]
 [-0.28923831]
 [-0.78532423]
 [-0.74806505]
 [-0.20232435]
 [ 1.62733087]
 [ 0.37297484]
 [-0.56882547]
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 [ 0.16802147]
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 [ 0.94361956]
 [-0.87967173]]
[[  4.15022239e-02  -1.52459204e-01   1.08347860e-01 ...,  -1.49844036e-01
    2.20917059e-01  -1.52402034e-01]
 [  4.32189934e-02   4.37972643e-02   9.28801839e-02 ...,  -2.46400340e-01
    4.14105071e-04   1.08976282e-01]
 [ -1.11475472e-01   3.59723401e-02   2.44316116e-01 ...,   1.60323594e-01
   -2.81894418e-01   6.66610651e-01]
 ..., 
 [ -1.84889203e-01  -2.01707613e-01  -1.45228710e-01 ...,   9.68220758e-02
   -9.04954643e-02  -6.91022287e-02]
 [ -2.79070870e-01  -2.32651141e-01  -7.00448060e-02 ...,  -1.22842073e-01
   -4.68887904e-02  -2.42311571e-01]
 [  4.66430000e-02  -1.39173142e-02  -7.77820712e-02 ...,   4.18197847e-02
    5.20183428e-01   1.70528115e-01]]
Progress: 17.4% ... Training loss: 0.257 ... Validation loss: 0.427[[ 0.29788748]
 [-0.29284421]
 [-0.78810525]
 [-0.75051284]
 [-0.20484925]
 [ 1.62394613]
 [ 0.36974719]
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 [ 0.72494887]
 [ 0.16483683]
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 [-0.05222264]
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 [ 0.36176395]
 [ 0.98871103]
 [-0.47778737]
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 [ 0.18823559]
 [ 0.03361804]
 [ 2.15338075]
 [-0.70589043]
 [-0.99828567]
 [ 0.58132078]
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 [ 0.94138312]
 [-0.88240963]]
[[  4.15234096e-02  -1.52469295e-01   1.08333936e-01 ...,  -1.49846042e-01
    2.21135112e-01  -1.52546670e-01]
 [  4.30622275e-02   4.39492852e-02   9.32427550e-02 ...,  -2.46355231e-01
    4.22060758e-05   1.09414637e-01]
 [ -1.11803039e-01   3.62992685e-02   2.45194682e-01 ...,   1.60441584e-01
   -2.82907263e-01   6.67661505e-01]
 ..., 
 [ -1.85079863e-01  -2.01528254e-01  -1.44799424e-01 ...,   9.68773926e-02
   -9.10705789e-02  -6.85766551e-02]
 [ -2.78980957e-01  -2.32739256e-01  -7.02865395e-02 ...,  -1.22867116e-01
   -4.66927668e-02  -2.42580307e-01]
 [  4.64849917e-02  -1.37470848e-02  -7.73874048e-02 ...,   4.18709242e-02
    5.20185451e-01   1.70849220e-01]]
Progress: 17.4% ... Training loss: 0.261 ... Validation loss: 0.428[[ 0.30539693]
 [-0.28683974]
 [-0.78239926]
 [-0.7417619 ]
 [-0.196482  ]
 [ 1.62882071]
 [ 0.37580302]
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 [-0.42523675]
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 [ 0.17148172]
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 [ 0.36922159]
 [ 0.99539202]
 [-0.46905367]
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 [ 0.19600231]
 [ 0.03884731]
 [ 2.15670569]
 [-0.69967904]
 [-0.98897319]
 [ 0.58579264]
 [-0.08583653]
 [ 0.95024204]
 [-0.8784567 ]]
[[  4.24362529e-02  -1.53358564e-01   1.06040584e-01 ...,  -1.50143754e-01
    2.23772650e-01  -1.54845254e-01]
 [  4.29326771e-02   4.40800852e-02   9.36197687e-02 ...,  -2.46322620e-01
   -3.03119920e-04   1.09824166e-01]
 [ -1.12043261e-01   3.65155416e-02   2.45520400e-01 ...,   1.60507145e-01
   -2.83545109e-01   6.67470152e-01]
 ..., 
 [ -1.85073036e-01  -2.01537651e-01  -1.44788778e-01 ...,   9.68761085e-02
   -9.11295973e-02  -6.87021332e-02]
 [ -2.78666798e-01  -2.33058878e-01  -7.10014501e-02 ...,  -1.22966779e-01
   -4.59453123e-02  -2.43303508e-01]
 [  4.72123769e-02  -1.44707887e-02  -7.93612856e-02 ...,   4.16541412e-02
    5.22420283e-01   1.68942982e-01]]
Progress: 17.4% ... Training loss: 0.257 ... Validation loss: 0.432[[ 0.29617672]
 [-0.29504581]
 [-0.78963526]
 [-0.75209908]
 [-0.20426571]
 [ 1.61992291]
 [ 0.36803843]
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 [ 0.72369248]
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 [ 0.27992061]
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 [ 0.03059224]
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 [-0.88609997]]
[[  4.19016409e-02  -1.52883202e-01   1.07405241e-01 ...,  -1.50011636e-01
    2.22200274e-01  -1.53588717e-01]
 [  4.29457888e-02   4.40752092e-02   9.36081357e-02 ...,  -2.46332369e-01
   -2.07505360e-04   1.09793162e-01]
 [ -1.12774385e-01   3.71866487e-02   2.47535087e-01 ...,   1.60696484e-01
   -2.85775127e-01   6.69772658e-01]
 ..., 
 [ -1.85702054e-01  -2.00968997e-01  -1.43176712e-01 ...,   9.70437156e-02
   -9.29814879e-02  -6.70190493e-02]
 [ -2.78549044e-01  -2.33168918e-01  -7.13032947e-02 ...,  -1.23002732e-01
   -4.56886809e-02  -2.43644059e-01]
 [  4.69697604e-02  -1.42267361e-02  -7.87235542e-02 ...,   4.17268781e-02
    5.22080949e-01   1.69501838e-01]]
Progress: 17.4% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.3042666 ]
 [-0.28586587]
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 [ 1.62883708]
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[[  4.22581996e-02  -1.53248090e-01   1.06389174e-01 ...,  -1.50124941e-01
    2.23390258e-01  -1.54941198e-01]
 [  4.29030828e-02   4.41202681e-02   9.36453995e-02 ...,  -2.46315240e-01
   -2.19511581e-04   1.09670217e-01]
 [ -1.11119702e-01   3.54867196e-02   2.43166798e-01 ...,   1.60145034e-01
   -2.81361667e-01   6.65688170e-01]
 ..., 
 [ -1.85688930e-01  -2.00972114e-01  -1.43262669e-01 ...,   9.70397045e-02
   -9.27849235e-02  -6.71661585e-02]
 [ -2.78303879e-01  -2.33418482e-01  -7.19095981e-02 ...,  -1.23081360e-01
   -4.49035093e-02  -2.44315772e-01]
 [  4.67468725e-02  -1.39740775e-02  -7.81669117e-02 ...,   4.18086599e-02
    5.21911610e-01   1.69827994e-01]]
Progress: 17.4% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.29990778]
 [-0.29042314]
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 [-0.75036105]
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 [ 1.62237364]
 [ 0.37052923]
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 [ 0.16578804]
 [ 0.28242656]
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 [ 0.98880428]
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 [ 0.03405829]
 [ 2.15240609]
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 [ 0.58164758]
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 [-0.87964324]]
[[  4.20816183e-02  -1.53094258e-01   1.06839901e-01 ...,  -1.50066733e-01
    2.21882361e-01  -1.54251378e-01]
 [  4.30482321e-02   4.39819947e-02   9.33081307e-02 ...,  -2.46354387e-01
    2.25736959e-04   1.09366987e-01]
 [ -1.12259810e-01   3.65621314e-02   2.46142820e-01 ...,   1.60455211e-01
   -2.84860351e-01   6.68859173e-01]
 ..., 
 [ -1.85822340e-01  -2.00848831e-01  -1.43035768e-01 ...,   9.70759255e-02
   -9.33653900e-02  -6.70091309e-02]
 [ -2.78123595e-01  -2.33589288e-01  -7.23563605e-02 ...,  -1.23126778e-01
   -4.45905312e-02  -2.44896771e-01]
 [  4.67437187e-02  -1.39691203e-02  -7.81488796e-02 ...,   4.18104616e-02
    5.21938987e-01   1.69762098e-01]]
Progress: 17.4% ... Training loss: 0.257 ... Validation loss: 0.430[[ 0.30591963]
 [-0.28537878]
 [-0.77910247]
 [-0.74452247]
 [-0.19465274]
 [ 1.62554785]
 [ 0.37584173]
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 [ 0.73188105]
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 [ 0.36874984]
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 [ 0.19660994]
 [ 0.03818321]
 [ 2.15547235]
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 [ 0.58585136]
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 [ 0.95268746]
 [-0.87624418]]
[[  4.22858022e-02  -1.53303981e-01   1.06295971e-01 ...,  -1.50119100e-01
    2.22433459e-01  -1.54519421e-01]
 [  4.31174963e-02   4.39147575e-02   9.31144501e-02 ...,  -2.46370962e-01
    4.56406085e-04   1.09263932e-01]
 [ -1.12616961e-01   3.69454167e-02   2.47045879e-01 ...,   1.60592607e-01
   -2.85548999e-01   6.69371220e-01]
 ..., 
 [ -1.85884967e-01  -2.00788036e-01  -1.42904881e-01 ...,   9.70906023e-02
   -9.34850379e-02  -6.69648091e-02]
 [ -2.77799535e-01  -2.33903505e-01  -7.31932985e-02 ...,  -1.23223015e-01
   -4.37109090e-02  -2.45830302e-01]
 [  4.63934594e-02  -1.36251348e-02  -7.71817966e-02 ...,   4.19208012e-02
    5.21310781e-01   1.70709696e-01]]
Progress: 17.4% ... Training loss: 0.256 ... Validation loss: 0.436[[ 0.3024743 ]
 [-0.28947517]
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 [-0.74846472]
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 [ 1.62486981]
 [ 0.37127107]
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 [ 0.16702401]
 [ 0.28235328]
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 [ 0.36342129]
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 [ 0.03321273]
 [ 2.15459871]
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 [ 0.58382148]
 [-0.09609121]
 [ 0.94643725]
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[[  4.21128226e-02  -1.53121841e-01   1.06796056e-01 ...,  -1.50064090e-01
    2.22154206e-01  -1.54101202e-01]
 [  4.31312698e-02   4.39009327e-02   9.30593629e-02 ...,  -2.46374115e-01
    4.96415533e-04   1.09149722e-01]
 [ -1.12102546e-01   3.64811905e-02   2.45960571e-01 ...,   1.60438330e-01
   -2.83865864e-01   6.68459771e-01]
 ..., 
 [ -1.85897182e-01  -2.00777780e-01  -1.42886259e-01 ...,   9.70932330e-02
   -9.34956209e-02  -6.69812503e-02]
 [ -2.78270016e-01  -2.33473447e-01  -7.21043972e-02 ...,  -1.23086242e-01
   -4.51152236e-02  -2.44930470e-01]
 [  4.60565588e-02  -1.32952564e-02  -7.63916491e-02 ...,   4.20204388e-02
    5.20703273e-01   1.71529100e-01]]
Progress: 17.4% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.30880439]
 [-0.28300257]
 [-0.77540966]
 [-0.74171553]
 [-0.19269717]
 [ 1.63278836]
 [ 0.37802952]
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 [ 0.732883  ]
 [ 0.17385611]
 [ 0.28827487]
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 [ 0.36983683]
 [ 0.99626189]
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 [ 0.19746642]
 [ 0.03655042]
 [ 2.15942146]
 [-0.69606632]
 [-0.98623589]
 [ 0.59046277]
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 [ 0.95242797]
 [-0.87066626]]
[[  4.24851531e-02  -1.53461158e-01   1.05869198e-01 ...,  -1.50181633e-01
    2.23584313e-01  -1.55102725e-01]
 [  4.30688678e-02   4.39673319e-02   9.31789018e-02 ...,  -2.46355349e-01
    4.12221713e-04   1.09216336e-01]
 [ -1.11048615e-01   3.54710694e-02   2.43504287e-01 ...,   1.60108258e-01
   -2.80936192e-01   6.66096437e-01]
 ..., 
 [ -1.85765443e-01  -2.00900088e-01  -1.43153595e-01 ...,   9.70585886e-02
   -9.31674865e-02  -6.71490656e-02]
 [ -2.77920542e-01  -2.33806685e-01  -7.30696271e-02 ...,  -1.23199486e-01
   -4.39976980e-02  -2.45973260e-01]
 [  4.64351947e-02  -1.36619313e-02  -7.73275693e-02 ...,   4.19009829e-02
    5.21990350e-01   1.70591690e-01]]
Progress: 17.4% ... Training loss: 0.258 ... Validation loss: 0.436[[ 0.28906688]
 [-0.30014925]
 [-0.78939321]
 [-0.75973836]
 [-0.20716654]
 [ 1.62174483]
 [ 0.36162398]
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 [ 0.15742187]
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 [ 0.35189857]
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 [ 0.17964891]
 [ 0.01823308]
 [ 2.14976547]
 [-0.71198459]
 [-1.00595268]
 [ 0.57548753]
 [-0.10360261]
 [ 0.92854151]
 [-0.88445819]]
[[  4.07930893e-02  -1.51895915e-01   1.10092415e-01 ...,  -1.49715840e-01
    2.19107490e-01  -1.50698281e-01]
 [  4.30617599e-02   4.39741069e-02   9.31935604e-02 ...,  -2.46352867e-01
    3.85778810e-04   1.09214332e-01]
 [ -1.11097064e-01   3.54323148e-02   2.44003499e-01 ...,   1.60099577e-01
   -2.82086322e-01   6.66943235e-01]
 ..., 
 [ -1.85633303e-01  -2.01024803e-01  -1.43477021e-01 ...,   9.70218268e-02
   -9.28741734e-02  -6.75032904e-02]
 [ -2.78000081e-01  -2.33737965e-01  -7.28974345e-02 ...,  -1.23180515e-01
   -4.41841984e-02  -2.45829736e-01]
 [  4.60163927e-02  -1.32423499e-02  -7.63884703e-02 ...,   4.20299913e-02
    5.21468690e-01   1.71440447e-01]]
Progress: 17.4% ... Training loss: 0.291 ... Validation loss: 0.455[[ 0.30739171]
 [-0.28418384]
 [-0.77403136]
 [-0.74274673]
 [-0.19155549]
 [ 1.63438632]
 [ 0.37711771]
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 [ 0.73163143]
 [ 0.17141284]
 [ 0.28681365]
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 [ 0.36819161]
 [ 0.9947989 ]
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 [ 0.19504311]
 [ 0.03511154]
 [ 2.15940062]
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 [ 0.59017456]
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 [ 0.94892365]
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[[ 0.0419375  -0.15308754  0.10711674 ..., -0.15012321  0.2223077
  -0.15384476]
 [ 0.04316647  0.04386662  0.09291654 ..., -0.24638595  0.00075128
   0.10900622]
 [-0.11025368  0.03455978  0.24160994 ...,  0.15980104 -0.2794137
   0.66420134]
 ..., 
 [-0.18570868 -0.20095909 -0.14322412 ...,  0.09704651 -0.09319163
  -0.06717555]
 [-0.27763003 -0.23411095 -0.07381228 ..., -0.12330863 -0.04322805
  -0.24661628]
 [ 0.04606119 -0.01326234 -0.07670668 ...,  0.04202773  0.52208847
   0.17096227]]
Progress: 17.4% ... Training loss: 0.257 ... Validation loss: 0.431[[ 0.3080339 ]
 [-0.28316687]
 [-0.77389666]
 [-0.74307914]
 [-0.19054229]
 [ 1.63430678]
 [ 0.37798681]
 [-0.56232578]
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 [ 0.73313497]
 [ 0.17332625]
 [ 0.28851304]
 [-0.04511269]
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 [ 0.37020505]
 [ 0.99695278]
 [-0.4667108 ]
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 [ 0.19695342]
 [ 0.03668346]
 [ 2.16086326]
 [-0.69707876]
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 [ 0.59146378]
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[[ 0.04229505 -0.15342211  0.10638175 ..., -0.15022765  0.22306347
  -0.15465369]
 [ 0.04316641  0.04387491  0.09287277 ..., -0.2463868   0.00084344
   0.10888748]
 [-0.11029181  0.03459692  0.24164202 ...,  0.15980752 -0.27974581
   0.6640612 ]
 ..., 
 [-0.18564086 -0.20102981 -0.14339105 ...,  0.09702847 -0.09322065
  -0.06738047]
 [-0.27740083 -0.23431258 -0.07435668 ..., -0.12337387 -0.04254809
  -0.24708674]
 [ 0.04618402 -0.01336231 -0.07700699 ...,  0.04199579  0.52244012
   0.17051257]]
Progress: 17.4% ... Training loss: 0.259 ... Validation loss: 0.434[[ 0.3055922 ]
 [-0.28625356]
 [-0.77641877]
 [-0.74638837]
 [-0.19430292]
 [ 1.6339305 ]
 [ 0.375577  ]
 [-0.56623993]
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 [ 0.73022733]
 [ 0.17100523]
 [ 0.28575762]
 [-0.04893151]
 [-0.67975434]
 [ 0.36700369]
 [ 0.99488058]
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 [ 0.19356521]
 [ 0.03405679]
 [ 2.16065025]
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 [-0.09201964]
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 [-0.86987849]]
[[  4.19560031e-02  -1.53110923e-01   1.07209134e-01 ...,  -1.50132633e-01
    2.22117110e-01  -1.53774321e-01]
 [  4.30682868e-02   4.39619552e-02   9.31233174e-02 ...,  -2.46358612e-01
    5.34574617e-04   1.09184098e-01]
 [ -1.10022359e-01   3.43178747e-02   2.41242146e-01 ...,   1.59732450e-01
   -2.79395488e-01   6.64158593e-01]
 ..., 
 [ -1.85444521e-01  -2.01202161e-01  -1.43801377e-01 ...,   9.69699632e-02
   -9.27936626e-02  -6.79054166e-02]
 [ -2.77450211e-01  -2.34275777e-01  -7.42785896e-02 ...,  -1.23360225e-01
   -4.26472389e-02  -2.46899970e-01]
 [  4.61973870e-02  -1.33668002e-02  -7.70355854e-02 ...,   4.19948649e-02
    5.22560551e-01   1.70542019e-01]]
Progress: 17.4% ... Training loss: 0.255 ... Validation loss: 0.428[[ 0.31014041]
 [-0.28257231]
 [-0.77158381]
 [-0.74437477]
 [-0.19205929]
 [ 1.63822894]
 [ 0.37967788]
 [-0.56306033]
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 [ 0.73574821]
 [ 0.17572997]
 [ 0.29006306]
 [-0.04458436]
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 [ 0.37216716]
 [ 1.00002397]
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 [-0.8662121 ]]
[[  4.29028080e-02  -1.53996142e-01   1.04949702e-01 ...,  -1.50431497e-01
    2.24451384e-01  -1.56199986e-01]
 [  4.31034178e-02   4.39293846e-02   9.30512465e-02 ...,  -2.46370574e-01
    6.32501568e-04   1.09130962e-01]
 [ -1.09320261e-01   3.36459314e-02   2.39405650e-01 ...,   1.59513116e-01
   -2.78060279e-01   6.62026242e-01]
 ..., 
 [ -1.84963481e-01  -2.01641915e-01  -1.45103047e-01 ...,   9.68232809e-02
   -9.16715387e-02  -6.94027107e-02]
 [ -2.77460905e-01  -2.34269179e-01  -7.42013339e-02 ...,  -1.23361885e-01
   -4.28034272e-02  -2.46759925e-01]
 [  4.61077273e-02  -1.32573026e-02  -7.67796607e-02 ...,   4.20294279e-02
    5.22502724e-01   1.70670545e-01]]
Progress: 17.4% ... Training loss: 0.264 ... Validation loss: 0.436[[ 0.30653357]
 [-0.28752157]
 [-0.77604766]
 [-0.74945525]
 [-0.19593394]
 [ 1.63142059]
 [ 0.3740204 ]
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 [ 0.17388083]
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 [-0.05199147]
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 [ 0.36776162]
 [ 0.99734139]
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 [ 0.19286181]
 [ 0.03300493]
 [ 2.1617834 ]
 [-0.7008045 ]
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 [ 0.58973442]
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 [-0.87167789]]
[[  4.22809570e-02  -1.53480657e-01   1.06454883e-01 ...,  -1.50276254e-01
    2.22640995e-01  -1.54780950e-01]
 [  4.30356823e-02   4.39963871e-02   9.32302707e-02 ...,  -2.46353917e-01
    4.38965437e-04   1.09321880e-01]
 [ -1.10337505e-01   3.45689331e-02   2.41927147e-01 ...,   1.59786363e-01
   -2.81209985e-01   6.64653323e-01]
 ..., 
 [ -1.85267188e-01  -2.01365852e-01  -1.44439944e-01 ...,   9.69041526e-02
   -9.26409894e-02  -6.85732900e-02]
 [ -2.77613548e-01  -2.34133444e-01  -7.38738000e-02 ...,  -1.23321519e-01
   -4.32553686e-02  -2.46424779e-01]
 [  4.56822236e-02  -1.28601414e-02  -7.57556580e-02 ...,   4.21510545e-02
    5.21787418e-01   1.71865359e-01]]
Progress: 17.5% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.30363284]
 [-0.28911895]
 [-0.77804019]
 [-0.75380985]
 [-0.19902178]
 [ 1.63230252]
 [ 0.37250011]
 [-0.57030023]
 [-0.42207593]
 [ 0.73282871]
 [ 0.17274219]
 [ 0.28390879]
 [-0.05488457]
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 [ 0.36548905]
 [ 0.99600823]
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 [ 0.190554  ]
 [ 0.02983793]
 [ 2.16336329]
 [-0.70407859]
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 [ 0.58882321]
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 [ 0.9480547 ]
 [-0.87275715]]
[[ 0.0416722  -0.15293867  0.10797915 ..., -0.15008673  0.22068776
  -0.15311249]
 [ 0.04314348  0.04390111  0.09292816 ..., -0.24638312  0.00095976
   0.10883632]
 [-0.10997372  0.03415151  0.24120094 ...,  0.15967158 -0.2802959
   0.66418331]
 ..., 
 [-0.18510934 -0.20153646 -0.14482864 ...,  0.09685711 -0.09263659
  -0.06881392]
 [-0.27800508 -0.23377799 -0.0730104  ..., -0.12320547 -0.04419042
  -0.24551485]
 [ 0.0457209  -0.01290426 -0.07584124 ...,  0.04213753  0.52194071
   0.17176432]]
Progress: 17.5% ... Training loss: 0.256 ... Validation loss: 0.428[[ 0.29559607]
 [-0.29613476]
 [-0.78244645]
 [-0.76099965]
 [-0.20601819]
 [ 1.63006024]
 [ 0.36571999]
 [-0.57817087]
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 [ 0.72679759]
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 [-0.48013914]
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 [ 0.02263522]
 [ 2.16096457]
 [-0.71046134]
 [-1.00734072]
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 [-0.10160251]
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 [-0.8765519 ]]
[[  4.12392464e-02  -1.52491684e-01   1.09071687e-01 ...,  -1.49959885e-01
    2.19750444e-01  -1.52147215e-01]
 [  4.29410889e-02   4.40986746e-02   9.33751046e-02 ...,  -2.46320105e-01
    4.27182510e-04   1.09435825e-01]
 [ -1.09171423e-01   3.32962219e-02   2.39464057e-01 ...,   1.59397124e-01
   -2.78711747e-01   6.62499014e-01]
 ..., 
 [ -1.84964899e-01  -2.01688202e-01  -1.45199198e-01 ...,   9.68086173e-02
   -9.22881020e-02  -6.92176494e-02]
 [ -2.78139151e-01  -2.33652713e-01  -7.26578925e-02 ...,  -1.23168931e-01
   -4.45607276e-02  -2.45142887e-01]
 [  4.53392814e-02  -1.25189054e-02  -7.48250586e-02 ...,   4.22635812e-02
    5.21483712e-01   1.72671481e-01]]
Progress: 17.5% ... Training loss: 0.269 ... Validation loss: 0.436[[ 0.30088394]
 [-0.29130219]
 [-0.78041865]
 [-0.75394723]
 [-0.20124996]
 [ 1.63299934]
 [ 0.3703858 ]
 [-0.57354878]
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 [ 0.72865618]
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 [ 0.02611962]
 [ 2.16245024]
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 [ 0.58676154]
 [-0.09761352]
 [ 0.94369121]
 [-0.87372173]]
[[  4.17792585e-02  -1.53055289e-01   1.07960090e-01 ...,  -1.50130837e-01
    2.21406953e-01  -1.52858945e-01]
 [  4.29410889e-02   4.40986746e-02   9.33751046e-02 ...,  -2.46320105e-01
    4.27182510e-04   1.09435825e-01]
 [ -1.09288314e-01   3.34364139e-02   2.39694192e-01 ...,   1.59456680e-01
   -2.78575663e-01   6.62496893e-01]
 ..., 
 [ -1.84813473e-01  -2.01874136e-01  -1.45508750e-01 ...,   9.67545784e-02
   -9.21238561e-02  -6.93481217e-02]
 [ -2.77930064e-01  -2.33866744e-01  -7.31400592e-02 ...,  -1.23236825e-01
   -4.40079750e-02  -2.45685236e-01]
 [  4.52183963e-02  -1.23578129e-02  -7.45307949e-02 ...,   4.23263715e-02
    5.21892181e-01   1.73123426e-01]]
Progress: 17.5% ... Training loss: 0.258 ... Validation loss: 0.428[[ 0.30775393]
 [-0.28423362]
 [-0.77544891]
 [-0.74856426]
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 [ 1.63591725]
 [ 0.37488984]
 [-0.56630636]
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[[  4.20960954e-02  -1.53393145e-01   1.07148863e-01 ...,  -1.50228006e-01
    2.22250362e-01  -1.53754248e-01]
 [  4.28619470e-02   4.41800823e-02   9.35102067e-02 ...,  -2.46291159e-01
    2.12540714e-04   1.09470507e-01]
 [ -1.09373770e-01   3.35200631e-02   2.39893286e-01 ...,   1.59494135e-01
   -2.79003878e-01   6.62478600e-01]
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 [ -1.84792454e-01  -2.01905273e-01  -1.45554966e-01 ...,   9.67471996e-02
   -9.20193727e-02  -6.93600393e-02]
 [ -2.77928395e-01  -2.33870039e-01  -7.31477940e-02 ...,  -1.23232912e-01
   -4.40420976e-02  -2.45679362e-01]
 [  4.55379560e-02  -1.26579505e-02  -7.53354955e-02 ...,   4.22260301e-02
    5.23025926e-01   1.72221062e-01]]
Progress: 17.5% ... Training loss: 0.257 ... Validation loss: 0.429[[ 0.29988307]
 [-0.29121288]
 [-0.78403472]
 [-0.75273274]
 [-0.20013796]
 [ 1.63408497]
 [ 0.3704378 ]
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[[  4.14210922e-02  -1.52750056e-01   1.08954352e-01 ...,  -1.50023667e-01
    2.21133032e-01  -1.51722219e-01]
 [  4.29768514e-02   4.40710175e-02   9.32372937e-02 ...,  -2.46325543e-01
    5.52359644e-04   1.09236545e-01]
 [ -1.09626558e-01   3.37822096e-02   2.40687839e-01 ...,   1.59565712e-01
   -2.79607997e-01   6.63344968e-01]
 ..., 
 [ -1.84917624e-01  -2.01797238e-01  -1.45239598e-01 ...,   9.67813161e-02
   -9.23716235e-02  -6.89679665e-02]
 [ -2.78057713e-01  -2.33759946e-01  -7.28656551e-02 ...,  -1.23194316e-01
   -4.42639819e-02  -2.45473200e-01]
 [  4.51586731e-02  -1.22695526e-02  -7.42948284e-02 ...,   4.23487891e-02
    5.22785777e-01   1.73177265e-01]]
Progress: 17.5% ... Training loss: 0.260 ... Validation loss: 0.428[[ 0.31555896]
 [-0.27782249]
 [-0.77380426]
 [-0.73917575]
 [-0.18799932]
 [ 1.63994248]
 [ 0.3831927 ]
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[[ 0.04211568 -0.15347255  0.1072681  ..., -0.15026221  0.22290292
  -0.15321776]
 [ 0.04310688  0.04394598  0.09290306 ..., -0.24636511  0.00097345
   0.1088841 ]
 [-0.1103819   0.03453184  0.24239169 ...,  0.15981    -0.28172874
   0.66491834]
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 [-0.18504346 -0.20168352 -0.14488431 ...,  0.09681375 -0.09276389
  -0.06858863]
 [-0.27792381 -0.23389364 -0.07321353 ..., -0.12323754 -0.04383244
  -0.24580989]
 [ 0.04603255 -0.01312815 -0.07650986 ...,  0.04206118  0.52484486
   0.1707753 ]]
Progress: 17.5% ... Training loss: 0.268 ... Validation loss: 0.447[[ 0.29686322]
 [-0.29371773]
 [-0.78859568]
 [-0.75619827]
 [-0.20293555]
 [ 1.62941767]
 [ 0.36781952]
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[[ 0.04055403 -0.15209424  0.11103136 ..., -0.14983294  0.21883456
  -0.14924793]
 [ 0.04306935  0.04397941  0.09299833 ..., -0.24635552  0.00089339
   0.10899463]
 [-0.11047033  0.03452985  0.24291307 ...,  0.15982108 -0.28305071
   0.66599587]
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 [-0.18566988 -0.20113753 -0.14344614 ...,  0.09698629 -0.09455322
  -0.06708653]
 [-0.27834194 -0.23353023 -0.07224672 ..., -0.12312511 -0.04499702
  -0.24478512]
 [ 0.04569148 -0.01281192 -0.07572339 ...,  0.04215843  0.52436094
   0.17149702]]
Progress: 17.5% ... Training loss: 0.271 ... Validation loss: 0.436[[ 0.3208489 ]
 [-0.2746418 ]
 [-0.77229439]
 [-0.73544781]
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 [ 1.64464653]
 [ 0.38741689]
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[[ 0.04198579 -0.15356806  0.10733652 ..., -0.15032402  0.22272023
  -0.15288892]
 [ 0.04311299  0.0439349   0.09289221 ..., -0.24636802  0.0010361
   0.10891917]
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   0.66426002]
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 [-0.18505966 -0.20174397 -0.14496972 ...,  0.09677902 -0.09303307
  -0.06873304]
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  -0.24500402]
 [ 0.04648143 -0.01360677 -0.07773382 ...,  0.04188792  0.52636825
   0.16957911]]
Progress: 17.5% ... Training loss: 0.282 ... Validation loss: 0.463[[ 0.2982893 ]
 [-0.29306075]
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 [ 1.63224927]
 [ 0.36949138]
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[[ 0.03986149 -0.15171175  0.11232283 ..., -0.14976799  0.21727846
  -0.14815511]
 [ 0.0431239   0.04392435  0.09288449 ..., -0.24637116  0.00107667
   0.10891896]
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   0.66582052]
 ..., 
 [-0.18543336 -0.20142337 -0.14416241 ...,  0.09687237 -0.09425046
  -0.06785255]
 [-0.27862472 -0.23330606 -0.07175658 ..., -0.12305936 -0.0457527
  -0.24419885]
 [ 0.04599649 -0.01315336 -0.07667903 ...,  0.0420243   0.52565561
   0.17042738]]
Progress: 17.5% ... Training loss: 0.269 ... Validation loss: 0.434[[ 0.31269646]
 [-0.27964348]
 [-0.77829069]
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 [ 1.63987153]
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[[ 0.04063919 -0.15249243  0.11042529 ..., -0.15002644  0.21917353
  -0.15012109]
 [ 0.04312642  0.04392169  0.09287377 ..., -0.24637156  0.0010904
   0.10889125]
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   0.66571609]
 ..., 
 [-0.18535666 -0.20150164 -0.14429532 ...,  0.09684673 -0.09401683
  -0.06789311]
 [-0.27823044 -0.2336891  -0.072775   ..., -0.12319363 -0.04466816
  -0.24526807]
 [ 0.04655459 -0.01372718 -0.07810666 ...,  0.04184172  0.5271808
   0.16903117]]
Progress: 17.5% ... Training loss: 0.259 ... Validation loss: 0.434[[ 0.30734613]
 [-0.28505964]
 [-0.78212734]
 [-0.74905195]
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 [ 1.63868867]
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[[ 0.04072819 -0.15260477  0.11017738 ..., -0.15006032  0.21935467
  -0.15032809]
 [ 0.0430479   0.04399152  0.09302739 ..., -0.24635078  0.00098104
   0.10899283]
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 ..., 
 [-0.185404   -0.20145802 -0.14418491 ...,  0.09685866 -0.09411674
  -0.06783356]
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  -0.24552757]
 [ 0.04684322 -0.01398519 -0.07882269 ...,  0.04176337  0.52788864
   0.16822666]]
Progress: 17.5% ... Training loss: 0.254 ... Validation loss: 0.425[[ 0.30697634]
 [-0.2863784 ]
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[[ 0.04076229 -0.15260485  0.11003948 ..., -0.15006747  0.21970775
  -0.15046776]
 [ 0.04296199  0.04407654  0.09318698 ..., -0.24632305  0.00080353
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   0.66596211]
 ..., 
 [-0.18537811 -0.20147009 -0.14425688 ...,  0.0968447  -0.09407959
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 [-0.27806357 -0.2338392  -0.07330404 ..., -0.12322975 -0.04461014
  -0.24584267]
 [ 0.04651846 -0.01366647 -0.07798537 ...,  0.04185921  0.52753773
   0.1692628 ]]
Progress: 17.5% ... Training loss: 0.255 ... Validation loss: 0.426[[ 0.3125588 ]
 [-0.28137476]
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 [ 1.64374881]
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[[ 0.04140588 -0.15316751  0.10855136 ..., -0.1502439   0.22145461
  -0.15210859]
 [ 0.04296199  0.04407654  0.09318698 ..., -0.24632305  0.00080353
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   0.66428329]
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 [-0.18511153 -0.20170942 -0.14490259 ...,  0.09676833 -0.09341954
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  -0.24560066]
 [ 0.04732927 -0.01443555 -0.07997124 ...,  0.04161376  0.52986655
   0.16711485]]
Progress: 17.5% ... Training loss: 0.261 ... Validation loss: 0.435[[ 0.30755041]
 [-0.28526851]
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[[  4.11362736e-02  -1.52910818e-01   1.09256309e-01 ...,  -1.50185817e-01
    2.20858914e-01  -1.51319913e-01]
 [  4.29001494e-02   4.41276476e-02   9.33358943e-02 ...,  -2.46308622e-01
    6.39114114e-04   1.09206368e-01]
 [ -1.09015475e-01   3.30519952e-02   2.39638763e-01 ...,   1.59321509e-01
   -2.79277324e-01   6.63021691e-01]
 ..., 
 [ -1.85251192e-01  -2.01585640e-01  -1.44560752e-01 ...,   9.68067028e-02
   -9.39184299e-02  -6.81693502e-02]
 [ -2.77846238e-01  -2.34027237e-01  -7.38201145e-02 ...,  -1.23292557e-01
   -4.41236001e-02  -2.46296613e-01]
 [  4.71027811e-02  -1.42034765e-02  -7.95295097e-02 ...,   4.16750807e-02
    5.29705943e-01   1.67346260e-01]]
Progress: 17.5% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.29756007]
 [-0.29340399]
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 [ 1.64037416]
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[[  4.10953139e-02  -1.52886674e-01   1.09311379e-01 ...,  -1.50176218e-01
    2.20749275e-01  -1.51135650e-01]
 [  4.27730294e-02   4.42430325e-02   9.36129503e-02 ...,  -2.46271292e-01
    2.49488435e-04   1.09551168e-01]
 [ -1.08865544e-01   3.28755793e-02   2.39662966e-01 ...,   1.59280608e-01
   -2.79306995e-01   6.62807452e-01]
 ..., 
 [ -1.85550591e-01  -2.01309648e-01  -1.43917599e-01 ...,   9.68961426e-02
   -9.47604635e-02  -6.73896836e-02]
 [ -2.78122500e-01  -2.33772268e-01  -7.32242678e-02 ...,  -1.23218105e-01
   -4.47320461e-02  -2.45614291e-01]
 [  4.68143542e-02  -1.39127413e-02  -7.88934544e-02 ...,   4.17708259e-02
    5.29473866e-01   1.68077429e-01]]
Progress: 17.6% ... Training loss: 0.260 ... Validation loss: 0.424[[ 0.29980364]
 [-0.29088092]
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[[ 0.04079624 -0.15261951  0.11000332 ..., -0.15009139  0.2198347
  -0.15042421]
 [ 0.04298889  0.04402777  0.09307506 ..., -0.2463388   0.00091058
   0.10895399]
 [-0.10948335  0.03338951  0.24106879 ...,  0.15943557 -0.28139613
   0.66433105]
 ..., 
 [-0.18602071 -0.20085717 -0.14274865 ...,  0.09704241 -0.09618736
  -0.06609204]
 [-0.27813681 -0.2337694  -0.07317173 ..., -0.12322305 -0.04458237
  -0.24540325]
 [ 0.04701958 -0.01412103 -0.07940426 ...,  0.041699    0.53007923
   0.16758975]]
Progress: 17.6% ... Training loss: 0.257 ... Validation loss: 0.422[[ 0.30386321]
 [-0.28733185]
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[[  4.12676648e-02  -1.53063728e-01   1.08612227e-01 ...,  -1.50239142e-01
    2.20913358e-01  -1.51490324e-01]
 [  4.28565228e-02   4.41599919e-02   9.33153017e-02 ...,  -2.46295622e-01
    5.97825935e-04   1.09138397e-01]
 [ -1.09838545e-01   3.36841124e-02   2.42245716e-01 ...,   1.59541078e-01
   -2.83047175e-01   6.65773176e-01]
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 [ -1.85963365e-01  -2.00905955e-01  -1.42919291e-01 ...,   9.70226518e-02
   -9.61815369e-02  -6.62290604e-02]
 [ -2.77909753e-01  -2.33991938e-01  -7.37502348e-02 ...,  -1.23291063e-01
   -4.39981531e-02  -2.45929767e-01]
 [  4.69032169e-02  -1.39849043e-02  -7.92268988e-02 ...,   4.17448651e-02
    5.29939067e-01   1.67568389e-01]]
Progress: 17.6% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.30048538]
 [-0.2901524 ]
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 [ 0.37314189]
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[[ 0.04070611 -0.15250523  0.11014745 ..., -0.15006431  0.21932455
  -0.14989612]
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 [-0.18580674 -0.20105324 -0.14334687 ...,  0.0969793  -0.09582856
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  -0.24594959]
 [ 0.04684713 -0.0139113  -0.0790934  ...,  0.04176992  0.53003091
   0.16766426]]
Progress: 17.6% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.31132348]
 [-0.28040114]
 [-0.77451657]
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 [ 1.64397167]
 [ 0.38258535]
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[[ 0.04178658 -0.15354674  0.1075269  ..., -0.15039377  0.2220845
  -0.15250892]
 [ 0.04315724  0.04386984  0.09266933 ..., -0.24639105  0.00157281
   0.108603  ]
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 [-0.18585641 -0.20101229 -0.14315059 ...,  0.09699104 -0.09591756
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  -0.24617492]
 [ 0.04739587 -0.01442482 -0.08052498 ...,  0.04159975  0.5317039
   0.16614001]]
Progress: 17.6% ... Training loss: 0.263 ... Validation loss: 0.435[[ 0.30204289]
 [-0.2891783 ]
 [-0.78173167]
 [-0.74650464]
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 [ 1.63836795]
 [ 0.37519623]
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[[ 0.0414473  -0.15324549  0.10847286 ..., -0.1503131   0.22128234
  -0.15165599]
 [ 0.04311779  0.04390886  0.09272992 ..., -0.24637844  0.00155442
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 [-0.1858121  -0.20105117 -0.1433048  ...,  0.09697618 -0.09582314
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  -0.24602459]
 [ 0.04729717 -0.01433435 -0.0802219  ...,  0.04162771  0.53166043
   0.16636285]]
Progress: 17.6% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.30422083]
 [-0.28721808]
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 [-0.19267643]
 [ 1.63633861]
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[[ 0.04159423 -0.15340703  0.10813592 ..., -0.15035902  0.22144516
  -0.15181174]
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 [-0.18547609 -0.20139286 -0.14415622 ...,  0.09687169 -0.09515219
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  -0.24561184]
 [ 0.0473748  -0.01439579 -0.08041534 ...,  0.04160543  0.53207389
   0.16611389]]
Progress: 17.6% ... Training loss: 0.254 ... Validation loss: 0.424[[ 0.29818956]
 [-0.29223289]
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 [ 1.63222373]
 [ 0.37084154]
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[[ 0.0408164  -0.15267041  0.11010604 ..., -0.15012649  0.21964931
  -0.14935526]
 [ 0.04319593  0.04383199  0.09249611 ..., -0.24640094  0.00178379
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   0.66932938]
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 [-0.18566571 -0.20121248 -0.14371815 ...,  0.09693374 -0.09566901
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 [-0.27770571 -0.23418857 -0.07430549 ..., -0.12334631 -0.04349263
  -0.24612471]
 [ 0.04688433 -0.01391483 -0.07917213 ...,  0.04176026  0.5310629
   0.16742747]]
Progress: 17.6% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.29957381]
 [-0.29118103]
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[[ 0.04088543 -0.15275774  0.10999457 ..., -0.15014734  0.21994702
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 [-0.18577806 -0.20110745 -0.14340459 ...,  0.09696621 -0.09598624
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  -0.2461999 ]
 [ 0.04697987 -0.01398355 -0.07943526 ...,  0.04174134  0.53164373
   0.16717053]]
Progress: 17.6% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.30141539]
 [-0.29024248]
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[[ 0.04122196 -0.15311007  0.10920833 ..., -0.15026301  0.22076451
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 [ 0.0469501  -0.01392326 -0.07937795 ...,  0.04177211  0.5320572
   0.16735061]]
Progress: 17.6% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.30352973]
 [-0.28817566]
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 [ 1.63284587]
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[[ 0.04132888 -0.15321689  0.10913884 ..., -0.15029715  0.22154873
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 [-0.18552898 -0.20135937 -0.14400897 ...,  0.09689733 -0.09550507
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  -0.24642977]
 [ 0.0464595  -0.0134301  -0.07811204 ...,  0.04193162  0.53142862
   0.16866106]]
Progress: 17.6% ... Training loss: 0.255 ... Validation loss: 0.425[[ 0.30820354]
 [-0.28517342]
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[[ 0.04165814 -0.15356474  0.10824283 ..., -0.15041654  0.22258359
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 [ 0.04346693  0.04357572  0.09180473 ..., -0.24648872  0.00270003
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 [-0.185551   -0.20133606 -0.14398001 ...,  0.09690532 -0.09556932
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  -0.24724831]
 [ 0.04657323 -0.0135424  -0.07834602 ...,  0.04189846  0.53193218
   0.16819883]]
Progress: 17.6% ... Training loss: 0.256 ... Validation loss: 0.432[[ 0.30416913]
 [-0.28807477]
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 [ 0.37713108]
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[[ 0.04128252 -0.15318055  0.1091898  ..., -0.15028737  0.22200319
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 [ 0.04343037  0.04361671  0.09187491 ..., -0.24647819  0.00268408
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 ..., 
 [-0.18561667 -0.20127641 -0.14383711 ...,  0.09692293 -0.09572075
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  -0.24714956]
 [ 0.0464961  -0.01346676 -0.078164   ...,  0.04193664  0.5322462
   0.16822337]]
Progress: 17.6% ... Training loss: 0.254 ... Validation loss: 0.424[[ 0.29796768]
 [-0.2935994 ]
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[[ 0.04117352 -0.15307519  0.1095167  ..., -0.1502571   0.22172809
  -0.14968476]
 [ 0.04319211  0.04384476  0.09230666 ..., -0.24640497  0.00203821
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 [-0.18592469 -0.20097487 -0.14327086 ...,  0.0970153  -0.09663724
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  -0.24587839]
 [ 0.0463066  -0.01327112 -0.0777007  ...,  0.04200201  0.53207023
   0.16870304]]
Progress: 17.6% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.31121692]
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[[ 0.04216231 -0.15404828  0.1070984  ..., -0.15056896  0.22407639
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 [ 0.04317451  0.04386247  0.09235474 ..., -0.24639927  0.00199717
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   0.66720627]
 ..., 
 [-0.18544326 -0.20144036 -0.14451758 ...,  0.09686367 -0.09557951
  -0.06757365]
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  -0.24643021]
 [ 0.0465015  -0.01345344 -0.07822899 ...,  0.04194624  0.5329226
   0.16822709]]
Progress: 17.6% ... Training loss: 0.265 ... Validation loss: 0.440[[ 0.29582052]
 [-0.2940842 ]
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[[ 0.0411484  -0.15308629  0.10964583 ..., -0.15028668  0.22186431
  -0.14931247]
 [ 0.04296283  0.04406198  0.09284008 ..., -0.2463457   0.00138402
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 ..., 
 [-0.1859418  -0.2009879  -0.14334893 ...,  0.09699365 -0.09697168
  -0.06632735]
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  -0.24682032]
 [ 0.04583045 -0.01275847 -0.07678256 ...,  0.04214845  0.53210826
   0.1698968 ]]
Progress: 17.7% ... Training loss: 0.258 ... Validation loss: 0.424[[ 0.30117655]
 [-0.28972546]
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[[ 0.04119707 -0.15316429  0.10972277 ..., -0.15030331  0.22154174
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   0.16928626]]
Progress: 17.7% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.29428536]
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   0.16906479]]
Progress: 17.7% ... Training loss: 0.260 ... Validation loss: 0.425[[ 0.30609445]
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   0.16770738]]
Progress: 17.7% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.30161391]
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   0.16732362]]
Progress: 17.7% ... Training loss: 0.255 ... Validation loss: 0.421[[ 0.29790098]
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   0.16801161]]
Progress: 17.7% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.30553658]
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[[ 0.04221509 -0.15412778  0.10731483 ..., -0.1505864   0.22478571
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   0.16753684]]
Progress: 17.7% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.29131536]
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[[ 0.04058995 -0.1525908   0.1114071  ..., -0.15013528  0.22022797
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   0.16682439]]
Progress: 17.7% ... Training loss: 0.268 ... Validation loss: 0.433[[ 0.29825467]
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   0.16658047]]
Progress: 17.7% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.30357367]
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[[ 0.04175449 -0.15373955  0.10817119 ..., -0.15048956  0.22368787
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   0.16572375]]
Progress: 17.7% ... Training loss: 0.257 ... Validation loss: 0.426[[ 0.30304682]
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[[ 0.04145306 -0.15346867  0.10887591 ..., -0.15041026  0.22261937
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   0.16614079]]
Progress: 17.7% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.29448285]
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[[ 0.04105584 -0.15311276  0.10994733 ..., -0.15030013  0.22170204
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   0.16649105]]
Progress: 17.7% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.30739001]
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[[ 0.04225214 -0.15432239  0.10690947 ..., -0.15069853  0.22539665
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   0.16731301]]
Progress: 17.7% ... Training loss: 0.262 ... Validation loss: 0.433[[ 0.29156383]
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[[ 0.04122006 -0.15335971  0.10927872 ..., -0.15041747  0.22293135
  -0.149463  ]
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   0.16766549]]
Progress: 17.7% ... Training loss: 0.268 ... Validation loss: 0.432[[ 0.29432186]
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[[ 0.04157839 -0.15367178  0.10851389 ..., -0.15053409  0.2242021
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   0.16738171]]
Progress: 17.7% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.30298559]
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[[ 0.04224582 -0.15435755  0.10676619 ..., -0.15076277  0.22628121
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   0.16753027]]
Progress: 17.8% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.29698889]
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   0.1675247 ]]
Progress: 17.8% ... Training loss: 0.255 ... Validation loss: 0.425[[ 0.29781967]
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   0.16768888]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.30024766]
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[[ 0.04214351 -0.15423848  0.10698568 ..., -0.15075128  0.2269547
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  -0.2462806 ]
 [ 0.04619335 -0.01290721 -0.07850417 ...,  0.04211655  0.53817589
   0.1679501 ]]
Progress: 17.8% ... Training loss: 0.253 ... Validation loss: 0.423[[ 0.29955393]
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[[ 0.04194565 -0.15406815  0.10749014 ..., -0.15068381  0.2262863
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  -0.24596708]
 [ 0.04597736 -0.01269639 -0.0779628  ...,  0.04218764  0.53769137
   0.16862026]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.423[[ 0.30054773]
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[[ 0.04233145 -0.1544104   0.10659172 ..., -0.15081002  0.22750765
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   0.16868201]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.30381255]
 [-0.28391199]
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[[ 0.04248103 -0.15454153  0.10628723 ..., -0.15084614  0.22792529
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 [ 0.04627531 -0.01297239 -0.07876905 ...,  0.04209525  0.53877774
   0.16785834]]
Progress: 17.8% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.29660984]
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[[ 0.04176106 -0.15385434  0.10801874 ..., -0.15062561  0.22592162
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   0.1683971 ]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.420[[ 0.29093124]
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[[ 0.04100363 -0.15307752  0.11006405 ..., -0.15038048  0.22417038
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   0.16814019]]
Progress: 17.8% ... Training loss: 0.262 ... Validation loss: 0.430[[ 0.29999399]
 [-0.28628878]
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[[ 0.04186385 -0.15392972  0.10803271 ..., -0.15068793  0.22647344
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   0.16790786]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.28945814]
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[[ 0.04127629 -0.15332529  0.10951091 ..., -0.15048418  0.22459185
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 [ 0.04602029 -0.01267653 -0.07824911 ...,  0.04218475  0.53924599
   0.1681115 ]]
Progress: 17.8% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.30489112]
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[[ 0.04215763 -0.15422295  0.10737859 ..., -0.15077646  0.22711345
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   0.16668653]]
Progress: 17.8% ... Training loss: 0.261 ... Validation loss: 0.429[[ 0.29375993]
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[[ 0.04173612 -0.1538282   0.10850101 ..., -0.1506654   0.22609856
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 [ 0.04627518 -0.01295336 -0.07909473 ...,  0.04208669  0.53999885
   0.16725164]]
Progress: 17.8% ... Training loss: 0.256 ... Validation loss: 0.422[[ 0.29664977]
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[[ 0.04183688 -0.15391611  0.10826334 ..., -0.15070136  0.22656193
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 [-0.18534364 -0.20172369 -0.14520879 ...,  0.09671102 -0.09632228
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 [ 0.04618257 -0.01285251 -0.07887898 ...,  0.04211661  0.53996759
   0.16748359]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.418[[ 0.29811248]
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[[ 0.04176302 -0.15386973  0.10841382 ..., -0.15067638  0.22645647
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 [ 0.0461827  -0.0128504  -0.0788821  ...,  0.04211386  0.54014321
   0.1674771 ]]
Progress: 17.8% ... Training loss: 0.254 ... Validation loss: 0.419[[ 0.29764871]
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[[ 0.04184338 -0.15391375  0.10836928 ..., -0.15069998  0.22682577
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 [ 0.046129   -0.01279105 -0.07867324 ...,  0.0421345   0.54020614
   0.16769722]]
Progress: 17.9% ... Training loss: 0.254 ... Validation loss: 0.419[[ 0.29679488]
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   0.16773851]]
Progress: 17.9% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.29665911]
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[[ 0.04217061 -0.15421746  0.10763471 ..., -0.15078817  0.22757164
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   0.16835963]]
Progress: 17.9% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.29277327]
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   0.16642828]]
Progress: 17.9% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.29236379]
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[[ 0.04202034 -0.15404474  0.10808434 ..., -0.15071632  0.22716653
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   0.16787228]]
Progress: 17.9% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.30115164]
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 [ 0.04575743 -0.01234549 -0.0778646  ...,  0.04228446  0.54080771
   0.16822881]]
Progress: 17.9% ... Training loss: 0.254 ... Validation loss: 0.426[[ 0.30384321]
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   0.16856905]]
Progress: 17.9% ... Training loss: 0.259 ... Validation loss: 0.429[[ 0.28732187]
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   0.17004791]]
Progress: 17.9% ... Training loss: 0.281 ... Validation loss: 0.443[[ 0.3105953 ]
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   0.16908443]]
Progress: 17.9% ... Training loss: 0.277 ... Validation loss: 0.456[[ 0.29831553]
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[[ 0.0418678  -0.15410131  0.10805389 ..., -0.15081491  0.22822965
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   0.16940442]]
Progress: 17.9% ... Training loss: 0.253 ... Validation loss: 0.423[[ 0.29468573]
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   0.16847212]]
Progress: 17.9% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.29895408]
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[[ 0.04226037 -0.1545246   0.1072785  ..., -0.15093331  0.22918799
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 [ 0.04548125 -0.01206087 -0.0775093  ...,  0.04234889  0.54164153
   0.16764085]]
Progress: 17.9% ... Training loss: 0.254 ... Validation loss: 0.425[[ 0.29536039]
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[[ 0.04212279 -0.15435888  0.10761537 ..., -0.15089258  0.22890091
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   0.16880418]]
Progress: 17.9% ... Training loss: 0.253 ... Validation loss: 0.421[[ 0.29133872]
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[[ 0.04187049 -0.15410816  0.10832624 ..., -0.15080873  0.22849402
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   0.17015993]]
Progress: 17.9% ... Training loss: 0.257 ... Validation loss: 0.424[[ 0.29546972]
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[[ 0.04198398 -0.15419194  0.10809892 ..., -0.15083716  0.22944019
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   0.17034882]]
Progress: 17.9% ... Training loss: 0.253 ... Validation loss: 0.421[[ 0.29385312]
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   0.17030473]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.422[[ 0.29534331]
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[[ 0.04129043 -0.15354061  0.10984881 ..., -0.15062285  0.22759757
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   0.16966191]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.423[[ 0.29838854]
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[[ 0.04160734 -0.15388905  0.10934298 ..., -0.15073748  0.22838641
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   0.16997717]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.425[[ 0.28730302]
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[[ 0.04091341 -0.1532085   0.11112042 ..., -0.15051265  0.22631773
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   0.16954864]]
Progress: 18.0% ... Training loss: 0.268 ... Validation loss: 0.437[[ 0.29869774]
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[[ 0.04152863 -0.15383887  0.10956374 ..., -0.1507255   0.22757944
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   0.16772504]]
Progress: 18.0% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.28703003]
 [-0.29414897]
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 [ 1.62716611]
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[[ 0.04077375 -0.15310866  0.11134308 ..., -0.15048415  0.22582002
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   0.16756596]]
Progress: 18.0% ... Training loss: 0.270 ... Validation loss: 0.442[[ 0.29990791]
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   0.16615194]]
Progress: 18.0% ... Training loss: 0.254 ... Validation loss: 0.430[[ 0.29654005]
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   0.16499115]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.427[[ 0.3058533 ]
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   0.16392698]]
Progress: 18.0% ... Training loss: 0.268 ... Validation loss: 0.440[[ 0.29484059]
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[[ 0.04198041 -0.15431135  0.1080227  ..., -0.15090395  0.22943764
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   0.16375982]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.422[[ 0.2992721 ]
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[[ 0.04212922 -0.15442273  0.10775635 ..., -0.15095324  0.23041091
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 [-0.18496633 -0.20230379 -0.14607    ...,  0.09648282 -0.09796815
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   0.16443147]]
Progress: 18.0% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.29050339]
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[[ 0.04203236 -0.15435027  0.10799619 ..., -0.15091663  0.23006186
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   0.16509401]]
Progress: 18.0% ... Training loss: 0.257 ... Validation loss: 0.424[[ 0.30011935]
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[[ 0.04233748 -0.1547021   0.10728262 ..., -0.15103263  0.23079094
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   0.16439998]]
Progress: 18.0% ... Training loss: 0.255 ... Validation loss: 0.422[[ 0.29718967]
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[[ 0.04252459 -0.15487973  0.10684806 ..., -0.15109438  0.23138604
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   0.16398579]]
Progress: 18.0% ... Training loss: 0.253 ... Validation loss: 0.420[[ 0.28901822]
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[[ 0.04149408 -0.15388861  0.10962519 ..., -0.15075275  0.22821255
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   0.16320059]]
Progress: 18.0% ... Training loss: 0.266 ... Validation loss: 0.434[[ 0.3082625 ]
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[[ 0.04235311 -0.15474333  0.10727358 ..., -0.1510366   0.23074781
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   0.16184373]]
Progress: 18.1% ... Training loss: 0.276 ... Validation loss: 0.450[[ 0.28117092]
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[[ 0.0403611  -0.15296056  0.11222064 ..., -0.15046091  0.2251356
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   0.1619302 ]]
Progress: 18.1% ... Training loss: 0.295 ... Validation loss: 0.463[[ 0.29635397]
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[[ 0.04056854 -0.15317427  0.11174517 ..., -0.15053831  0.22556644
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   0.1602826 ]]
Progress: 18.1% ... Training loss: 0.252 ... Validation loss: 0.425[[ 0.29791985]
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   0.1602108 ]]
Progress: 18.1% ... Training loss: 0.253 ... Validation loss: 0.427[[ 0.2994332 ]
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  -0.24505716]
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   0.16005974]]
Progress: 18.1% ... Training loss: 0.254 ... Validation loss: 0.429[[ 0.29597594]
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[[ 0.04051994 -0.15312552  0.11199917 ..., -0.15053881  0.22557996
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  -0.244208  ]
 [ 0.04767821 -0.01409792 -0.08395725 ...,  0.0415981   0.55291613
   0.1604754 ]]
Progress: 18.1% ... Training loss: 0.252 ... Validation loss: 0.424[[ 0.29975011]
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[[ 0.04069585 -0.15328845  0.11163901 ..., -0.15059952  0.22626302
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   0.16006604]]
Progress: 18.1% ... Training loss: 0.254 ... Validation loss: 0.426[[ 0.28849946]
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[[ 0.03976806 -0.15239211  0.11404961 ..., -0.15031127  0.22361167
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   0.15967263]]
Progress: 18.1% ... Training loss: 0.264 ... Validation loss: 0.433[[ 0.29730615]
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[[ 0.04012491 -0.15270282  0.11329029 ..., -0.15044203  0.22506167
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 [ 0.04783802 -0.01419807 -0.0841457  ...,  0.04157002  0.55423444
   0.16023287]]
Progress: 18.1% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.29404557]
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[[ 0.03983659 -0.15238322  0.1140651  ..., -0.15035249  0.2244877
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   0.16027997]]
Progress: 18.1% ... Training loss: 0.253 ... Validation loss: 0.424[[ 0.29859282]
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[[ 0.040482   -0.15305505  0.11259762 ..., -0.15057174  0.22610874
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 [ 0.04759743 -0.01392972 -0.08360352 ...,  0.04165063  0.55420377
   0.16079984]]
Progress: 18.1% ... Training loss: 0.253 ... Validation loss: 0.429[[ 0.2974226 ]
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[[ 0.04096868 -0.15349795  0.11142319 ..., -0.15072332  0.22741506
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 [ 0.04691403 -0.01325891 -0.0818556  ...,  0.04186788  0.55268926
   0.16258568]]
Progress: 18.1% ... Training loss: 0.254 ... Validation loss: 0.428[[ 0.28953966]
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[[ 0.0404155  -0.15298419  0.11295561 ..., -0.15054836  0.2260908
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 [-0.18460731 -0.20280627 -0.14725277 ...,  0.09624994 -0.09784075
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   0.1633791 ]]
Progress: 18.1% ... Training loss: 0.260 ... Validation loss: 0.429[[ 0.29335086]
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[[ 0.04033162 -0.15286153  0.11338612 ..., -0.15050256  0.22576953
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   0.16316028]]
Progress: 18.1% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.29191873]
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[[ 0.04053929 -0.15304667  0.1129331  ..., -0.1505596   0.2263666
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   0.16321766]]
Progress: 18.1% ... Training loss: 0.254 ... Validation loss: 0.428[[ 0.29909892]
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   0.16210552]]
Progress: 18.2% ... Training loss: 0.255 ... Validation loss: 0.434[[ 0.293179  ]
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   0.16230182]]
Progress: 18.2% ... Training loss: 0.253 ... Validation loss: 0.428[[ 0.28943775]
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[[ 0.04067811 -0.15312074  0.11246601 ..., -0.15056815  0.22688687
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   0.16179396]]
Progress: 18.2% ... Training loss: 0.258 ... Validation loss: 0.429[[ 0.29394407]
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   0.16085655]]
Progress: 18.2% ... Training loss: 0.253 ... Validation loss: 0.429[[ 0.29579836]
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   0.16124985]]
Progress: 18.2% ... Training loss: 0.255 ... Validation loss: 0.429[[ 0.28513575]
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[[ 0.04163411 -0.15402289  0.11038962 ..., -0.15090085  0.22973743
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   0.16253434]]
Progress: 18.2% ... Training loss: 0.260 ... Validation loss: 0.430[[ 0.28980552]
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   0.16260272]]
Progress: 18.2% ... Training loss: 0.253 ... Validation loss: 0.424[[ 0.28558675]
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   0.16330771]]
Progress: 18.2% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.28791918]
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   0.16487747]]
Progress: 18.2% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.28540053]
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[[ 0.0426853  -0.15500161  0.10764295 ..., -0.15126154  0.23403039
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   0.16565055]]
Progress: 18.2% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.280181  ]
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[[ 0.04184    -0.15413613  0.10991519 ..., -0.15097434  0.23146718
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 [ 0.04586138 -0.01196378 -0.07908017 ...,  0.04230874  0.55473615
   0.16472329]]
Progress: 18.2% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.29226553]
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[[ 0.04254085 -0.15488209  0.10832454 ..., -0.15122851  0.23337759
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   0.16443181]]
Progress: 18.2% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.29841741]
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[[ 0.04317701 -0.1555122   0.10667074 ..., -0.1514422   0.23519995
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   0.16266373]]
Progress: 18.2% ... Training loss: 0.271 ... Validation loss: 0.448[[ 0.28637976]
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[[ 0.04188973 -0.15433792  0.10991967 ..., -0.15104745  0.23152577
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   0.16353126]]
Progress: 18.2% ... Training loss: 0.254 ... Validation loss: 0.423[[ 0.28980302]
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   0.16386118]]
Progress: 18.2% ... Training loss: 0.253 ... Validation loss: 0.427[[ 0.28457029]
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   0.16432599]]
Progress: 18.3% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.29036873]
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   0.16391342]]
Progress: 18.3% ... Training loss: 0.255 ... Validation loss: 0.429[[ 0.29105038]
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[[ 0.04290303 -0.15531196  0.1073727  ..., -0.15140025  0.23444185
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   0.1642231 ]]
Progress: 18.3% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.29017789]
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   0.1652865 ]]
Progress: 18.3% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.29305965]
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   0.16559329]]
Progress: 18.3% ... Training loss: 0.257 ... Validation loss: 0.429[[ 0.29105802]
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   0.1671205 ]]
Progress: 18.3% ... Training loss: 0.254 ... Validation loss: 0.425[[ 0.29299141]
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   0.16598086]]
Progress: 18.3% ... Training loss: 0.255 ... Validation loss: 0.426[[ 0.28924162]
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[[ 0.04216059 -0.15453748  0.10934392 ..., -0.15112799  0.23345028
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   0.16597475]]
Progress: 18.3% ... Training loss: 0.253 ... Validation loss: 0.420[[ 0.29967987]
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[[ 0.04322984 -0.15550535  0.10658325 ..., -0.15146688  0.23684925
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   0.16477336]]
Progress: 18.3% ... Training loss: 0.268 ... Validation loss: 0.438[[ 0.27822561]
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   0.16582145]]
Progress: 18.3% ... Training loss: 0.281 ... Validation loss: 0.445[[ 0.30328014]
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[[ 0.0429358  -0.15545101  0.10708028 ..., -0.15151151  0.23634319
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   0.16383516]]
Progress: 18.3% ... Training loss: 0.276 ... Validation loss: 0.446[[ 0.28425946]
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[[ 0.04116799 -0.15388496  0.11138813 ..., -0.1510238   0.23098782
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   0.16402113]]
Progress: 18.3% ... Training loss: 0.266 ... Validation loss: 0.433[[ 0.29123587]
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[[ 0.0414686  -0.15417736  0.11060337 ..., -0.15113313  0.23193882
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   0.16340168]]
Progress: 18.3% ... Training loss: 0.252 ... Validation loss: 0.423[[ 0.28898056]
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[[ 0.04094705 -0.15369023  0.11209728 ..., -0.15097352  0.23042241
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   0.16304971]]
Progress: 18.3% ... Training loss: 0.254 ... Validation loss: 0.424[[ 0.30093146]
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   0.16318572]]
Progress: 18.3% ... Training loss: 0.260 ... Validation loss: 0.441[[ 0.29443705]
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   0.16361285]]
Progress: 18.4% ... Training loss: 0.253 ... Validation loss: 0.429[[ 0.29310008]
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   0.1634107 ]]
Progress: 18.4% ... Training loss: 0.253 ... Validation loss: 0.429[[ 0.29927003]
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   0.16221658]]
Progress: 18.4% ... Training loss: 0.259 ... Validation loss: 0.438[[ 0.28846201]
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   0.16272631]]
Progress: 18.4% ... Training loss: 0.255 ... Validation loss: 0.423[[ 0.29295088]
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[[ 0.04092275 -0.15366459  0.11261283 ..., -0.15101175  0.23158944
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   0.16289727]]
Progress: 18.4% ... Training loss: 0.253 ... Validation loss: 0.427[[ 0.3026088 ]
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   0.16286609]]
Progress: 18.4% ... Training loss: 0.263 ... Validation loss: 0.445[[ 0.29187643]
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   0.16464456]]
Progress: 18.4% ... Training loss: 0.252 ... Validation loss: 0.422[[ 0.3021489 ]
 [-0.27543569]
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[[ 0.04104105 -0.15382447  0.1121363  ..., -0.15105281  0.2326154
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   0.16255498]]
Progress: 18.4% ... Training loss: 0.266 ... Validation loss: 0.440[[ 0.28801581]
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 [ 0.04562323 -0.01155491 -0.0793546  ...,  0.0423814   0.5617001
   0.16331639]]
Progress: 18.4% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.28554825]
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[[ 0.04105042 -0.15375597  0.11228103 ..., -0.15105237  0.23301305
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 [-0.18566733 -0.20198755 -0.1448474  ...,  0.0964101  -0.10403684
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   0.16386429]]
Progress: 18.4% ... Training loss: 0.256 ... Validation loss: 0.423[[ 0.29075269]
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[[ 0.04108561 -0.1538127   0.11246572 ..., -0.15107173  0.23394532
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 [-0.18559855 -0.20205761 -0.14497181 ...,  0.09638361 -0.10383608
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   0.16498307]]
Progress: 18.4% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.28353855]
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[[ 0.04073516 -0.15349913  0.11337861 ..., -0.15095817  0.23283638
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   0.16429486]]
Progress: 18.4% ... Training loss: 0.261 ... Validation loss: 0.428[[ 0.29139942]
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[[ 0.0414075  -0.15414867  0.11162398 ..., -0.1511848   0.23494557
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 [-0.18573299 -0.20192611 -0.14470371 ...,  0.09641644 -0.10434895
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   0.16240057]]
Progress: 18.4% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.29820907]
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[[ 0.04211899 -0.15487968  0.10984072 ..., -0.15141806  0.23674287
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   0.16195535]]
Progress: 18.4% ... Training loss: 0.261 ... Validation loss: 0.434[[ 0.28516691]
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[[ 0.04139187 -0.15412523  0.11180156 ..., -0.15117843  0.23500046
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   0.16206164]]
Progress: 18.4% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.28994121]
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   0.16136613]]
Progress: 18.5% ... Training loss: 0.253 ... Validation loss: 0.421[[ 0.28408557]
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[[ 0.04163934 -0.15436827  0.11133483 ..., -0.15126872  0.23573719
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   0.1625302 ]]
Progress: 18.5% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.29035821]
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   0.16290423]]
Progress: 18.5% ... Training loss: 0.252 ... Validation loss: 0.427[[ 0.28595916]
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   0.16249885]]
Progress: 18.5% ... Training loss: 0.255 ... Validation loss: 0.426[[ 0.28939743]
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[[ 0.0414442  -0.15423017  0.11241132 ..., -0.15123592  0.23479751
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   0.16249675]]
Progress: 18.5% ... Training loss: 0.252 ... Validation loss: 0.427[[ 0.28572619]
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[[ 0.04103074 -0.15380927  0.11342784 ..., -0.15110434  0.23385585
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   0.16420118]]
Progress: 18.5% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.28768423]
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   0.16290724]]
Progress: 18.5% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.2912175 ]
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[[ 0.04117456 -0.15397013  0.11312511 ..., -0.15116454  0.23444582
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 [ 0.04536049 -0.01114147 -0.07900891 ...,  0.04251049  0.56588292
   0.16332966]]
Progress: 18.5% ... Training loss: 0.252 ... Validation loss: 0.427[[ 0.29307731]
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[[ 0.04131669 -0.15411708  0.113084   ..., -0.15122051  0.23517432
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   0.16312422]]
Progress: 18.5% ... Training loss: 0.254 ... Validation loss: 0.428[[ 0.28430207]
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   0.16399154]]
Progress: 18.5% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.29854425]
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[[ 0.04226303 -0.15506233  0.11070803 ..., -0.15155029  0.23814751
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   0.16306053]]
Progress: 18.5% ... Training loss: 0.265 ... Validation loss: 0.439[[ 0.28704188]
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[[ 0.04124637 -0.15410981  0.11340987 ..., -0.15126491  0.23490615
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   0.16378474]]
Progress: 18.5% ... Training loss: 0.253 ... Validation loss: 0.422[[ 0.29501726]
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[[ 0.04173438 -0.15458644  0.11204956 ..., -0.15144115  0.23579288
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 [ 0.04546071 -0.01119704 -0.0793626  ...,  0.04247381  0.56767942
   0.16270892]]
Progress: 18.5% ... Training loss: 0.254 ... Validation loss: 0.429[[ 0.28021463]
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[[ 0.04103584 -0.15388679  0.11399618 ..., -0.15122349  0.23359995
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   0.16309607]]
Progress: 18.5% ... Training loss: 0.271 ... Validation loss: 0.435[[ 0.29940111]
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[[ 0.0423364  -0.1551731   0.11053884 ..., -0.15169441  0.23766279
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   0.16168888]]
Progress: 18.5% ... Training loss: 0.272 ... Validation loss: 0.448[[ 0.28876497]
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[[ 0.04169204 -0.15457487  0.11231698 ..., -0.1515271   0.23587433
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   0.16329374]]
Progress: 18.6% ... Training loss: 0.251 ... Validation loss: 0.421[[ 0.28886115]
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[[ 0.04112683 -0.15398244  0.11382976 ..., -0.15133147  0.2348839
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   0.16262107]]
Progress: 18.6% ... Training loss: 0.251 ... Validation loss: 0.422[[ 0.29509388]
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[[ 0.04154644 -0.15441206  0.11268277 ..., -0.15146216  0.23591251
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   0.16254939]]
Progress: 18.6% ... Training loss: 0.257 ... Validation loss: 0.429[[ 0.28434473]
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[[ 0.04125168 -0.15410936  0.11347292 ..., -0.15135827  0.2350071
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   0.16302768]]
Progress: 18.6% ... Training loss: 0.254 ... Validation loss: 0.421[[ 0.29379752]
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[[ 0.04179454 -0.15469579  0.11226935 ..., -0.15153925  0.23645699
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   0.16180612]]
Progress: 18.6% ... Training loss: 0.255 ... Validation loss: 0.431[[ 0.29278607]
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   0.1613484 ]]
Progress: 18.6% ... Training loss: 0.252 ... Validation loss: 0.427[[ 0.29401524]
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[[ 0.04196804 -0.15484897  0.11181013 ..., -0.15157356  0.23763237
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   0.16102141]]
Progress: 18.6% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.28843277]
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[[ 0.04131377 -0.15419346  0.1134382  ..., -0.15136818  0.2360451
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   0.16242054]]
Progress: 18.6% ... Training loss: 0.252 ... Validation loss: 0.420[[ 0.29032345]
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[[ 0.04161709 -0.15450265  0.11281081 ..., -0.15147049  0.2371687
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   0.16237439]]
Progress: 18.6% ... Training loss: 0.251 ... Validation loss: 0.422[[ 0.28680114]
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[[ 0.04116342 -0.15404247  0.114073   ..., -0.15132387  0.236342
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   0.16204267]]
Progress: 18.6% ... Training loss: 0.251 ... Validation loss: 0.419[[ 0.28638005]
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[[ 0.0406758  -0.15353256  0.1154281  ..., -0.15117299  0.23518269
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   0.16312794]]
Progress: 18.6% ... Training loss: 0.252 ... Validation loss: 0.421[[ 0.2900792 ]
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[[ 0.04110759 -0.15395483  0.11444252 ..., -0.15131725  0.23656598
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   0.16238175]]
Progress: 18.6% ... Training loss: 0.251 ... Validation loss: 0.421[[ 0.28023074]
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[[ 0.04019256 -0.15305262  0.11683866 ..., -0.15101834  0.23376328
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 [-0.18501122 -0.202739   -0.14695098 ...,  0.0960768  -0.10404297
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   0.16348337]]
Progress: 18.6% ... Training loss: 0.263 ... Validation loss: 0.428[[ 0.29301347]
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   0.16298198]]
Progress: 18.6% ... Training loss: 0.255 ... Validation loss: 0.427[[ 0.28160667]
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   0.16439978]]
Progress: 18.6% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.28954003]
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   0.16403363]]
Progress: 18.7% ... Training loss: 0.252 ... Validation loss: 0.421[[ 0.28594851]
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   0.16458118]]
Progress: 18.7% ... Training loss: 0.252 ... Validation loss: 0.420[[ 0.28445039]
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   0.16401972]]
Progress: 18.7% ... Training loss: 0.254 ... Validation loss: 0.425[[ 0.28568348]
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[[ 0.03931355 -0.15224234  0.11954525 ..., -0.15079173  0.23106574
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   0.16377354]]
Progress: 18.7% ... Training loss: 0.253 ... Validation loss: 0.425[[ 0.2925096 ]
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   0.16310061]]
Progress: 18.7% ... Training loss: 0.253 ... Validation loss: 0.424[[ 0.28761084]
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Progress: 18.7% ... Training loss: 0.251 ... Validation loss: 0.422[[ 0.28105218]
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   0.1633531 ]]
Progress: 18.7% ... Training loss: 0.260 ... Validation loss: 0.432[[ 0.28741207]
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[[ 0.04001151 -0.15296988  0.11807801 ..., -0.1510362   0.23339039
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   0.16329084]]
Progress: 18.7% ... Training loss: 0.251 ... Validation loss: 0.424[[ 0.29254805]
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[[ 0.0411783  -0.15410887  0.11501705 ..., -0.15142558  0.23665219
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   0.16177408]]
Progress: 18.7% ... Training loss: 0.254 ... Validation loss: 0.426[[ 0.28226797]
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[[ 0.04025585 -0.15324904  0.11739193 ..., -0.15113431  0.23401028
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   0.16266573]]
Progress: 18.7% ... Training loss: 0.261 ... Validation loss: 0.431[[ 0.29837368]
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[[ 0.04127789 -0.15428245  0.11477295 ..., -0.15150843  0.23730893
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   0.16080266]]
Progress: 18.7% ... Training loss: 0.262 ... Validation loss: 0.440[[ 0.28491293]
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[[ 0.03994947 -0.1530611   0.11798817 ..., -0.15111616  0.23384426
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   0.16043054]]
Progress: 18.7% ... Training loss: 0.256 ... Validation loss: 0.426[[ 0.29706406]
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[[ 0.0406751  -0.15380333  0.11614414 ..., -0.15135325  0.23589796
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   0.15995504]]
Progress: 18.7% ... Training loss: 0.258 ... Validation loss: 0.433[[ 0.29084828]
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   0.16147763]]
Progress: 18.7% ... Training loss: 0.251 ... Validation loss: 0.424[[ 0.29318895]
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[[ 0.03957274 -0.15275296  0.11896421 ..., -0.15101308  0.23306608
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   0.16148407]]
Progress: 18.7% ... Training loss: 0.251 ... Validation loss: 0.425[[ 0.2928155 ]
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   0.16182078]]
Progress: 18.8% ... Training loss: 0.251 ... Validation loss: 0.424[[ 0.29741771]
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[[ 0.03982574 -0.15300308  0.11858318 ..., -0.15109245  0.23420403
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 [ 0.04531449 -0.01087977 -0.07959626 ...,  0.04246141  0.57632268
   0.16206586]]
Progress: 18.8% ... Training loss: 0.256 ... Validation loss: 0.432[[ 0.2949626 ]
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   0.16118914]]
Progress: 18.8% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.29093832]
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[[ 0.03925326 -0.15252576  0.12011339 ..., -0.15092599  0.23182485
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 [ 0.04541644 -0.01096742 -0.07981554 ...,  0.0424378   0.57638457
   0.16176121]]
Progress: 18.8% ... Training loss: 0.252 ... Validation loss: 0.424[[ 0.29371754]
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[[ 0.03937861 -0.15257882  0.11989257 ..., -0.15095371  0.23268066
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   0.16121148]]
Progress: 18.8% ... Training loss: 0.251 ... Validation loss: 0.425[[ 0.29505735]
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   0.16002326]]
Progress: 18.8% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.28606364]
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[[ 0.03858178 -0.15184552  0.12214451 ..., -0.15069135  0.23031372
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   0.16176318]]
Progress: 18.8% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.29867595]
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[[ 0.03930639 -0.15251527  0.12017143 ..., -0.15093024  0.23293263
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   0.15904557]]
Progress: 18.8% ... Training loss: 0.256 ... Validation loss: 0.436[[ 0.29669441]
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[[ 0.03890553 -0.15213541  0.1213706  ..., -0.1508103   0.23204817
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 [ 0.04613395 -0.01163936 -0.08209042 ...,  0.0421798   0.58036152
   0.15933887]]
Progress: 18.8% ... Training loss: 0.253 ... Validation loss: 0.434[[ 0.29333881]
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[[ 0.03847407 -0.1517315   0.12251822 ..., -0.15068135  0.23149133
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 [ 0.04554781 -0.0110784  -0.08053332 ...,  0.04236133  0.57948288
   0.16085463]]
Progress: 18.8% ... Training loss: 0.251 ... Validation loss: 0.426[[ 0.29228182]
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[[ 0.03878502 -0.15200078  0.12174812 ..., -0.15076972  0.23258608
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 [-0.1858756  -0.20203003 -0.14487949 ...,  0.09628428 -0.10808014
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   0.16001633]]
Progress: 18.8% ... Training loss: 0.251 ... Validation loss: 0.424[[ 0.29060675]
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[[ 0.03868544 -0.15185182  0.12205331 ..., -0.15071554  0.23265501
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   0.15971807]]
Progress: 18.8% ... Training loss: 0.250 ... Validation loss: 0.422[[ 0.2918923 ]
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[[ 0.03920578 -0.15235636  0.12091489 ..., -0.15087093  0.23449249
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   0.16006055]]
Progress: 18.8% ... Training loss: 0.250 ... Validation loss: 0.424[[ 0.29260364]
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[[ 0.03895699 -0.15208927  0.12172027 ..., -0.15078158  0.23352779
  -0.13636345]
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   0.16027306]]
Progress: 18.8% ... Training loss: 0.251 ... Validation loss: 0.427[[ 0.2947726 ]
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   0.16086459]]
Progress: 18.8% ... Training loss: 0.252 ... Validation loss: 0.432[[ 0.29189724]
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[[ 0.03931708 -0.1524293   0.12115397 ..., -0.15088035  0.23439196
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  -0.24711767]
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   0.16068254]]
Progress: 18.9% ... Training loss: 0.251 ... Validation loss: 0.427[[ 0.28978375]
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   0.16025675]]
Progress: 18.9% ... Training loss: 0.252 ... Validation loss: 0.425[[ 0.29315727]
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   0.16070821]]
Progress: 18.9% ... Training loss: 0.251 ... Validation loss: 0.426[[ 0.28330522]
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[[ 0.03899498 -0.1521714   0.12201522 ..., -0.150764    0.23341377
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   0.16037103]]
Progress: 18.9% ... Training loss: 0.266 ... Validation loss: 0.432[[ 0.29214998]
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[[ 0.03977893 -0.15296699  0.11986258 ..., -0.15106493  0.23577714
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   0.15970082]]
Progress: 18.9% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.29529333]
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[[ 0.03993307 -0.15314784  0.11952799 ..., -0.15110983  0.23632658
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   0.15976171]]
Progress: 18.9% ... Training loss: 0.252 ... Validation loss: 0.429[[ 0.28694197]
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[[ 0.03911221 -0.15238334  0.12173115 ..., -0.15084954  0.23414927
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   0.16080199]]
Progress: 18.9% ... Training loss: 0.259 ... Validation loss: 0.425[[ 0.30156753]
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[[ 0.0397697  -0.15304706  0.11998446 ..., -0.15107784  0.23584144
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   0.16044973]]
Progress: 18.9% ... Training loss: 0.262 ... Validation loss: 0.442[[ 0.29378774]
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[[ 0.0397217  -0.15297109  0.12004644 ..., -0.15105655  0.23597675
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 [-0.18659113 -0.20140215 -0.14326052 ...,  0.09649118 -0.11106399
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 [ 0.04523717 -0.01067117 -0.0797993  ...,  0.04249096  0.58338357
   0.16122841]]
Progress: 18.9% ... Training loss: 0.251 ... Validation loss: 0.423[[ 0.2933145 ]
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[[ 0.03981112 -0.15304875  0.11993399 ..., -0.15108855  0.23640317
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   0.16190211]]
Progress: 18.9% ... Training loss: 0.251 ... Validation loss: 0.423[[ 0.30043716]
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[[ 0.04128581 -0.15442377  0.11623273 ..., -0.15155982  0.24055256
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 [-0.18611587 -0.2018455  -0.14450144 ...,  0.09633872 -0.10988648
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   0.16198675]]
Progress: 18.9% ... Training loss: 0.266 ... Validation loss: 0.445[[ 0.27773959]
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[[ 0.03938589 -0.15266047  0.12094225 ..., -0.15099714  0.23583805
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 [-0.18666479 -0.20134244 -0.14316911 ...,  0.09649678 -0.11154234
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   0.16304971]]
Progress: 18.9% ... Training loss: 0.280 ... Validation loss: 0.437[[ 0.29643435]
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[[ 0.04025033 -0.15357809  0.11863661 ..., -0.15135262  0.23843136
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Progress: 18.9% ... Training loss: 0.256 ... Validation loss: 0.433[[ 0.27667274]
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   0.16322618]]
Progress: 18.9% ... Training loss: 0.280 ... Validation loss: 0.437[[ 0.29109943]
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Progress: 18.9% ... Training loss: 0.251 ... Validation loss: 0.422[[ 0.29269817]
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   0.16327614]]
Progress: 19.0% ... Training loss: 0.253 ... Validation loss: 0.425[[ 0.28855809]
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   0.16243655]]
Progress: 19.0% ... Training loss: 0.251 ... Validation loss: 0.418[[ 0.29463417]
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   0.16012212]]
Progress: 19.0% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.2764467 ]
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   0.16100432]]
Progress: 19.0% ... Training loss: 0.267 ... Validation loss: 0.427[[ 0.28377782]
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Progress: 19.0% ... Training loss: 0.253 ... Validation loss: 0.418[[ 0.28756276]
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   0.16344033]]
Progress: 19.0% ... Training loss: 0.250 ... Validation loss: 0.417[[ 0.29186174]
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Progress: 19.0% ... Training loss: 0.250 ... Validation loss: 0.424[[ 0.29118319]
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   0.1633351 ]]
Progress: 19.0% ... Training loss: 0.250 ... Validation loss: 0.426[[ 0.28752828]
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[[ 0.03885404 -0.15239232  0.12303582 ..., -0.15099936  0.23602384
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   0.1640588 ]]
Progress: 19.0% ... Training loss: 0.251 ... Validation loss: 0.423[[ 0.29808213]
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[[ 0.03939055 -0.15298208  0.1217535  ..., -0.15119399  0.23786568
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   0.16398422]]
Progress: 19.0% ... Training loss: 0.260 ... Validation loss: 0.441[[ 0.28910609]
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   0.16392906]]
Progress: 19.0% ... Training loss: 0.250 ... Validation loss: 0.421[[ 0.28635239]
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Progress: 19.0% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.2833032 ]
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   0.16507107]]
Progress: 19.0% ... Training loss: 0.255 ... Validation loss: 0.420[[ 0.29338877]
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Progress: 19.0% ... Training loss: 0.258 ... Validation loss: 0.429[[ 0.28667935]
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   0.16333003]]
Progress: 19.0% ... Training loss: 0.251 ... Validation loss: 0.415[[ 0.28379483]
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 [ 0.04438194 -0.009611   -0.07828155 ...,  0.04279468  0.58814824
   0.16299247]]
Progress: 19.1% ... Training loss: 0.252 ... Validation loss: 0.414[[ 0.28462813]
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   0.16354931]]
Progress: 19.1% ... Training loss: 0.252 ... Validation loss: 0.415[[ 0.27746237]
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   0.16492393]]
Progress: 19.1% ... Training loss: 0.274 ... Validation loss: 0.438[[ 0.30290943]
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   0.16308384]]
Progress: 19.1% ... Training loss: 0.276 ... Validation loss: 0.457[[ 0.28507749]
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   0.16471071]]
Progress: 19.1% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.30378779]
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   0.16312222]]
Progress: 19.1% ... Training loss: 0.281 ... Validation loss: 0.456[[ 0.28816206]
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   0.16226909]]
Progress: 19.1% ... Training loss: 0.251 ... Validation loss: 0.419[[ 0.29183134]
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[[ 0.03784231 -0.15163173  0.12546101 ..., -0.15090038  0.2347714
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   0.16121289]]
Progress: 19.1% ... Training loss: 0.250 ... Validation loss: 0.420[[ 0.28521208]
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   0.16087893]]
Progress: 19.1% ... Training loss: 0.254 ... Validation loss: 0.420[[ 0.29434645]
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   0.16056116]]
Progress: 19.1% ... Training loss: 0.252 ... Validation loss: 0.425[[ 0.29165712]
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   0.16077444]]
Progress: 19.1% ... Training loss: 0.250 ... Validation loss: 0.421[[ 0.2969491 ]
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   0.16060275]]
Progress: 19.1% ... Training loss: 0.257 ... Validation loss: 0.429[[ 0.28591781]
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   0.16180432]]
Progress: 19.1% ... Training loss: 0.253 ... Validation loss: 0.419[[ 0.29007553]
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   0.16106433]]
Progress: 19.1% ... Training loss: 0.249 ... Validation loss: 0.418[[ 0.28785116]
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   0.16099969]]
Progress: 19.1% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.29000064]
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   0.16028623]]
Progress: 19.2% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.2845564 ]
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   0.16089633]]
Progress: 19.2% ... Training loss: 0.253 ... Validation loss: 0.419[[ 0.29137578]
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[[ 0.03907386 -0.15272128  0.122883   ..., -0.15127877  0.23967158
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   0.16026117]]
Progress: 19.2% ... Training loss: 0.251 ... Validation loss: 0.422[[ 0.28716032]
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   0.15896869]]
Progress: 19.2% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.28447182]
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   0.15976982]]
Progress: 19.2% ... Training loss: 0.252 ... Validation loss: 0.419[[ 0.29464823]
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[[ 0.03882057 -0.15246744  0.12387948 ..., -0.1512261   0.23842795
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   0.15802183]]
Progress: 19.2% ... Training loss: 0.257 ... Validation loss: 0.428[[ 0.28491088]
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[[ 0.03920697 -0.15280334  0.1230039  ..., -0.15133228  0.23973063
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   0.15902614]]
Progress: 19.2% ... Training loss: 0.250 ... Validation loss: 0.416[[ 0.28571531]
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[[ 0.03933048 -0.15296274  0.12275867 ..., -0.15136982  0.23998546
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   0.15891803]]
Progress: 19.2% ... Training loss: 0.249 ... Validation loss: 0.417[[ 0.29879969]
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[[ 0.03988492 -0.15352902  0.12124443 ..., -0.1515413   0.24125143
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   0.15759177]]
Progress: 19.2% ... Training loss: 0.274 ... Validation loss: 0.449[[ 0.28014394]
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[[ 0.0388615  -0.15258545  0.12381233 ..., -0.15126024  0.23847235
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   0.1597646 ]]
Progress: 19.2% ... Training loss: 0.258 ... Validation loss: 0.426[[ 0.29363092]
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[[ 0.03988734 -0.1536278   0.12120166 ..., -0.15162396  0.24168256
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   0.15611874]]
Progress: 19.2% ... Training loss: 0.258 ... Validation loss: 0.433[[ 0.27862443]
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Progress: 19.2% ... Training loss: 0.258 ... Validation loss: 0.425[[ 0.28113338]
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   0.15877824]]
Progress: 19.2% ... Training loss: 0.251 ... Validation loss: 0.421[[ 0.28837002]
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   0.15821182]]
Progress: 19.2% ... Training loss: 0.252 ... Validation loss: 0.426[[ 0.27517934]
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   0.15790392]]
Progress: 19.2% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.29380907]
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   0.15707926]]
Progress: 19.3% ... Training loss: 0.272 ... Validation loss: 0.444[[ 0.28856008]
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   0.15642601]]
Progress: 19.3% ... Training loss: 0.255 ... Validation loss: 0.426[[ 0.26996963]
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   0.15701392]]
Progress: 19.3% ... Training loss: 0.276 ... Validation loss: 0.442[[ 0.28619931]
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Progress: 19.3% ... Training loss: 0.252 ... Validation loss: 0.422[[ 0.28626523]
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[[ 0.03794179 -0.1517236   0.12633049 ..., -0.15107976  0.23834202
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   0.15668897]]
Progress: 19.3% ... Training loss: 0.254 ... Validation loss: 0.422[[ 0.28076386]
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   0.1578755 ]]
Progress: 19.3% ... Training loss: 0.249 ... Validation loss: 0.416[[ 0.28132036]
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 [ 0.0455231  -0.0105027  -0.08244032 ...,  0.04239382  0.60359412
   0.15772734]]
Progress: 19.3% ... Training loss: 0.249 ... Validation loss: 0.417[[ 0.28786768]
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[[ 0.03874567 -0.15252498  0.1245686  ..., -0.15132221  0.24039485
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Progress: 19.3% ... Training loss: 0.256 ... Validation loss: 0.424[[ 0.29103565]
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[[ 0.03861378 -0.15239055  0.12505936 ..., -0.15129826  0.24049755
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   0.15674132]]
Progress: 19.3% ... Training loss: 0.262 ... Validation loss: 0.428[[ 0.28422554]
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[[ 0.03862198 -0.15241941  0.12497639 ..., -0.15131546  0.24021939
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   0.15685441]]
Progress: 19.3% ... Training loss: 0.250 ... Validation loss: 0.415[[ 0.27527041]
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[[ 0.03861907 -0.15242774  0.1249069  ..., -0.15132776  0.24063733
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   0.15749474]]
Progress: 19.3% ... Training loss: 0.258 ... Validation loss: 0.419[[ 0.28586384]
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   0.1566769 ]]
Progress: 19.3% ... Training loss: 0.251 ... Validation loss: 0.416[[ 0.27412836]
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   0.15833545]]
Progress: 19.3% ... Training loss: 0.264 ... Validation loss: 0.425[[ 0.28903351]
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   0.15770354]]
Progress: 19.3% ... Training loss: 0.251 ... Validation loss: 0.420[[ 0.28846904]
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   0.15736467]]
Progress: 19.3% ... Training loss: 0.251 ... Validation loss: 0.420[[ 0.29155011]
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   0.15655376]]
Progress: 19.4% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.27438231]
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[[ 0.03889637 -0.15286713  0.12453868 ..., -0.15148946  0.24194335
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   0.15631399]]
Progress: 19.4% ... Training loss: 0.267 ... Validation loss: 0.429[[ 0.2820684 ]
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   0.15495815]]
Progress: 19.4% ... Training loss: 0.249 ... Validation loss: 0.416[[ 0.28603724]
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   0.15301577]]
Progress: 19.4% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.27105841]
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   0.15579636]]
Progress: 19.4% ... Training loss: 0.278 ... Validation loss: 0.438[[ 0.29002564]
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   0.15459174]]
Progress: 19.4% ... Training loss: 0.257 ... Validation loss: 0.434[[ 0.28141468]
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   0.15541683]]
Progress: 19.4% ... Training loss: 0.249 ... Validation loss: 0.419[[ 0.28271522]
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[[ 0.03911351 -0.15311732  0.12455317 ..., -0.15164758  0.24518248
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   0.15498671]]
Progress: 19.4% ... Training loss: 0.250 ... Validation loss: 0.421[[ 0.2827468 ]
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[[ 0.03865174 -0.15266558  0.12585896 ..., -0.15150528  0.24388829
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   0.15486069]]
Progress: 19.4% ... Training loss: 0.250 ... Validation loss: 0.421[[ 0.27888797]
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[[ 0.03754654 -0.15156589  0.12875126 ..., -0.15116465  0.2407484
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   0.15508442]]
Progress: 19.4% ... Training loss: 0.256 ... Validation loss: 0.425[[ 0.28430238]
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[[ 0.03763231 -0.15163988  0.12867789 ..., -0.15118851  0.24156908
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   0.15513297]]
Progress: 19.4% ... Training loss: 0.251 ... Validation loss: 0.423[[ 0.28316025]
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[[ 0.03725662 -0.15125222  0.12972004 ..., -0.15106121  0.24062026
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   0.15517648]]
Progress: 19.4% ... Training loss: 0.250 ... Validation loss: 0.422[[ 0.28292734]
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[[ 0.03701562 -0.15099497  0.13036435 ..., -0.15097351  0.24025191
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   0.15600883]]
Progress: 19.4% ... Training loss: 0.250 ... Validation loss: 0.422[[ 0.28205841]
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[[ 0.03692176 -0.15088366  0.13055096 ..., -0.15093061  0.24014921
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   0.15723065]]
Progress: 19.4% ... Training loss: 0.249 ... Validation loss: 0.422[[ 0.29427632]
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 [ 0.0452126  -0.01000809 -0.08233442 ...,  0.04251621  0.6111589
   0.15741595]]
Progress: 19.4% ... Training loss: 0.271 ... Validation loss: 0.442[[ 0.27852659]
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[[ 0.03733191 -0.15132264  0.12956435 ..., -0.15110373  0.24190195
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   0.15756732]]
Progress: 19.5% ... Training loss: 0.253 ... Validation loss: 0.423[[ 0.27626196]
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[[ 0.03661312 -0.15057886  0.13164264 ..., -0.1508538   0.23953313
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   0.15765107]]
Progress: 19.5% ... Training loss: 0.258 ... Validation loss: 0.430[[ 0.28105826]
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[[ 0.03680934 -0.15078563  0.13118632 ..., -0.15092042  0.23985876
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   0.15772709]]
Progress: 19.5% ... Training loss: 0.252 ... Validation loss: 0.425[[ 0.28681819]
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[[ 0.03691697 -0.15093043  0.13080709 ..., -0.15094812  0.23992849
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   0.15624797]]
Progress: 19.5% ... Training loss: 0.250 ... Validation loss: 0.427[[ 0.2854412 ]
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   0.15676037]]
Progress: 19.5% ... Training loss: 0.249 ... Validation loss: 0.425[[ 0.28447599]
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[[ 0.03683023 -0.15086496  0.13118871 ..., -0.15091285  0.2400145
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   0.15548766]]
Progress: 19.5% ... Training loss: 0.251 ... Validation loss: 0.426[[ 0.29549052]
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[[ 0.03749939 -0.15153602  0.12947664 ..., -0.15113243  0.24229914
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   0.15496308]]
Progress: 19.5% ... Training loss: 0.264 ... Validation loss: 0.447[[ 0.2727987 ]
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[[ 0.0355802  -0.149753    0.13441141 ..., -0.15058672  0.23719164
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   0.1576314 ]]
Progress: 19.5% ... Training loss: 0.284 ... Validation loss: 0.446[[ 0.29419365]
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[[ 0.0371386  -0.15140144  0.1303335  ..., -0.1511647   0.24241512
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 [-0.18477223 -0.20394938 -0.14849115 ...,  0.09549754 -0.11090861
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   0.1576643 ]]
Progress: 19.5% ... Training loss: 0.262 ... Validation loss: 0.440[[ 0.28109466]
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[[ 0.03595502 -0.15032241  0.1332267  ..., -0.1508279   0.23888802
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   0.15741977]]
Progress: 19.5% ... Training loss: 0.254 ... Validation loss: 0.424[[ 0.286244  ]
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[[ 0.03607271 -0.15042002  0.13271905 ..., -0.15085732  0.23976172
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   0.15651313]]
Progress: 19.5% ... Training loss: 0.249 ... Validation loss: 0.423[[ 0.28043446]
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[[ 0.0353086  -0.1496405   0.13475432 ..., -0.15061868  0.23824394
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   0.15713054]]
Progress: 19.5% ... Training loss: 0.254 ... Validation loss: 0.425[[ 0.29465643]
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[[ 0.03689191 -0.15124137  0.13057632 ..., -0.15113299  0.24270112
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   0.15526437]]
Progress: 19.5% ... Training loss: 0.265 ... Validation loss: 0.445[[ 0.27734214]
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   0.15646605]]
Progress: 19.5% ... Training loss: 0.261 ... Validation loss: 0.427[[ 0.28344885]
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   0.15688375]]
Progress: 19.5% ... Training loss: 0.250 ... Validation loss: 0.421[[ 0.28711428]
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[[ 0.03564512 -0.15015663  0.13354195 ..., -0.15082699  0.23832239
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   0.15584768]]
Progress: 19.6% ... Training loss: 0.249 ... Validation loss: 0.424[[ 0.28382334]
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[[ 0.03553623 -0.15004909  0.13396329 ..., -0.15079295  0.23843504
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   0.15647304]]
Progress: 19.6% ... Training loss: 0.250 ... Validation loss: 0.422[[ 0.29137358]
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   0.15525602]]
Progress: 19.6% ... Training loss: 0.255 ... Validation loss: 0.432[[ 0.28318872]
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   0.15489198]]
Progress: 19.6% ... Training loss: 0.249 ... Validation loss: 0.420[[ 0.28645046]
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[[ 0.03576034 -0.15025629  0.13335659 ..., -0.15089539  0.23900312
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   0.15467063]]
Progress: 19.6% ... Training loss: 0.249 ... Validation loss: 0.421[[ 0.28735774]
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[[ 0.03604132 -0.1505213   0.13270027 ..., -0.15098035  0.24012265
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   0.15401467]]
Progress: 19.6% ... Training loss: 0.250 ... Validation loss: 0.423[[ 0.2721241 ]
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[[ 0.03512391 -0.1496365   0.13527997 ..., -0.15070887  0.23733821
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   0.15444335]]
Progress: 19.6% ... Training loss: 0.269 ... Validation loss: 0.434[[ 0.28932847]
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[[ 0.0357848  -0.15034185  0.13340146 ..., -0.15094459  0.23961617
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   0.1538559 ]]
Progress: 19.6% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.28353207]
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[[ 0.03596163 -0.15052137  0.13305282 ..., -0.15100067  0.23984373
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   0.15409225]]
Progress: 19.6% ... Training loss: 0.248 ... Validation loss: 0.419[[ 0.28694759]
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[[ 0.03605928 -0.15064909  0.13295809 ..., -0.15104703  0.23995689
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   0.15363228]]
Progress: 19.6% ... Training loss: 0.249 ... Validation loss: 0.422[[ 0.29078268]
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   0.15243849]]
Progress: 19.6% ... Training loss: 0.255 ... Validation loss: 0.430[[ 0.28005046]
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   0.15219706]]
Progress: 19.6% ... Training loss: 0.255 ... Validation loss: 0.423[[ 0.29498383]
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   0.15018833]]
Progress: 19.6% ... Training loss: 0.261 ... Validation loss: 0.444[[ 0.2724624 ]
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[[ 0.03512152 -0.14981056  0.13576772 ..., -0.15081622  0.23665193
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   0.15192711]]
Progress: 19.6% ... Training loss: 0.281 ... Validation loss: 0.440[[ 0.28999268]
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[[ 0.03626976 -0.15105956  0.1325489  ..., -0.15123442  0.2399438
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   0.15107942]]
Progress: 19.6% ... Training loss: 0.251 ... Validation loss: 0.432[[ 0.27806407]
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[[ 0.0358488  -0.15064439  0.13357802 ..., -0.15111858  0.2391433
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   0.15215407]]
Progress: 19.7% ... Training loss: 0.257 ... Validation loss: 0.423[[ 0.2903781 ]
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   0.15175496]]
Progress: 19.7% ... Training loss: 0.252 ... Validation loss: 0.432[[ 0.27977661]
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[[ 0.03542908 -0.150259    0.13473031 ..., -0.1510148   0.23812312
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   0.15299872]]
Progress: 19.7% ... Training loss: 0.256 ... Validation loss: 0.425[[ 0.28730322]
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[[ 0.03643341 -0.15130521  0.13203579 ..., -0.15133772  0.2411316
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   0.15280272]]
Progress: 19.7% ... Training loss: 0.249 ... Validation loss: 0.427[[ 0.28927397]
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[[ 0.03661675 -0.15151765  0.13165221 ..., -0.15139713  0.24185543
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   0.15349343]]
Progress: 19.7% ... Training loss: 0.250 ... Validation loss: 0.430[[ 0.27266076]
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   0.15389533]]
Progress: 19.7% ... Training loss: 0.283 ... Validation loss: 0.441[[ 0.29633272]
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   0.15097619]]
Progress: 19.7% ... Training loss: 0.268 ... Validation loss: 0.455[[ 0.29018478]
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[[ 0.03680876 -0.15168553  0.13130027 ..., -0.15147503  0.24255327
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   0.15253451]]
Progress: 19.7% ... Training loss: 0.252 ... Validation loss: 0.434[[ 0.28500753]
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[[ 0.03642307 -0.15128774  0.1324009  ..., -0.1513737   0.24214029
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   0.15326729]]
Progress: 19.7% ... Training loss: 0.248 ... Validation loss: 0.422[[ 0.2938676 ]
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[[ 0.03698672 -0.15189809  0.1309528  ..., -0.15155854  0.24347194
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   0.15265449]]
Progress: 19.7% ... Training loss: 0.260 ... Validation loss: 0.443[[ 0.29399728]
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[[ 0.03679811 -0.15174048  0.1313778  ..., -0.15151203  0.24276121
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   0.15343537]]
Progress: 19.7% ... Training loss: 0.260 ... Validation loss: 0.443[[ 0.28026381]
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[[ 0.03584291 -0.15080632  0.13391666 ..., -0.15124311  0.24018805
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   0.1528171 ]]
Progress: 19.7% ... Training loss: 0.252 ... Validation loss: 0.419[[ 0.28709546]
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[[ 0.03653017 -0.151548    0.13218005 ..., -0.15148187  0.24173039
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   0.1531522 ]]
Progress: 19.7% ... Training loss: 0.248 ... Validation loss: 0.428[[ 0.28604141]
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[[ 0.03643193 -0.15146083  0.13252345 ..., -0.15145496  0.24149735
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   0.15402895]]
Progress: 19.7% ... Training loss: 0.249 ... Validation loss: 0.426[[ 0.29234174]
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   0.15313148]]
Progress: 19.7% ... Training loss: 0.253 ... Validation loss: 0.446[[ 0.28360593]
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[[ 0.0373733  -0.1524325   0.13042896 ..., -0.15176514  0.2439877
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   0.15306505]]
Progress: 19.8% ... Training loss: 0.250 ... Validation loss: 0.423[[ 0.2948907 ]
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[[ 0.03781886 -0.15288499  0.12935835 ..., -0.15190591  0.24535945
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   0.15192284]]
Progress: 19.8% ... Training loss: 0.261 ... Validation loss: 0.448[[ 0.28267288]
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[[ 0.03744743 -0.1525405   0.13049259 ..., -0.15179925  0.2438917
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   0.15296929]]
Progress: 19.8% ... Training loss: 0.249 ... Validation loss: 0.419[[ 0.29771441]
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[[ 0.03822256 -0.15333806  0.12843166 ..., -0.15205535  0.24598903
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   0.15164637]]
Progress: 19.8% ... Training loss: 0.271 ... Validation loss: 0.460[[ 0.27824773]
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[[ 0.03714205 -0.15227769  0.13117934 ..., -0.15176159  0.24372542
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 [ 0.0454168  -0.01009735 -0.08474405 ...,  0.04235607  0.62997754
   0.15333233]]
Progress: 19.8% ... Training loss: 0.255 ... Validation loss: 0.419[[ 0.29039981]
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[[ 0.03761777 -0.15278607  0.12986523 ..., -0.15190984  0.2453574
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   0.15375972]]
Progress: 19.8% ... Training loss: 0.252 ... Validation loss: 0.430[[ 0.27873148]
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[[ 0.03656941 -0.15178288  0.13262818 ..., -0.15159042  0.24295937
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   0.1555766 ]]
Progress: 19.8% ... Training loss: 0.256 ... Validation loss: 0.422[[ 0.28828743]
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[[ 0.03728802 -0.15252798  0.13069786 ..., -0.15183223  0.24544427
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 [ 0.04508631 -0.00977244 -0.08381492 ...,  0.04246487  0.6306848
   0.15479371]]
Progress: 19.8% ... Training loss: 0.249 ... Validation loss: 0.425[[ 0.27975445]
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[[ 0.03693017 -0.15210181  0.13167633 ..., -0.1517193   0.24476909
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   0.15479345]]
Progress: 19.8% ... Training loss: 0.249 ... Validation loss: 0.418[[ 0.2880158 ]
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[[ 0.03712457 -0.1523038   0.13108512 ..., -0.15177897  0.2452716
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   0.15337139]]
Progress: 19.8% ... Training loss: 0.251 ... Validation loss: 0.425[[ 0.28306594]
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   0.15433535]]
Progress: 19.8% ... Training loss: 0.247 ... Validation loss: 0.419[[ 0.27903247]
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[[ 0.03639428 -0.15156282  0.13307909 ..., -0.15156632  0.24309551
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   0.15243726]]
Progress: 19.8% ... Training loss: 0.251 ... Validation loss: 0.420[[ 0.28231419]
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[[ 0.0362339  -0.1513708   0.13347016 ..., -0.15150673  0.24257257
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 [ 0.04586677 -0.01051855 -0.08597693 ...,  0.04221992  0.63430223
   0.15217466]]
Progress: 19.8% ... Training loss: 0.247 ... Validation loss: 0.420[[ 0.28955705]
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   0.15202865]]
Progress: 19.8% ... Training loss: 0.252 ... Validation loss: 0.431[[ 0.2825811 ]
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   0.15263771]]
Progress: 19.8% ... Training loss: 0.248 ... Validation loss: 0.419[[ 0.28113104]
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   0.1522583 ]]
Progress: 19.9% ... Training loss: 0.248 ... Validation loss: 0.419[[ 0.2729579 ]
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[[ 0.0358749  -0.15095218  0.13464745 ..., -0.15139008  0.24241822
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   0.15298834]]
Progress: 19.9% ... Training loss: 0.265 ... Validation loss: 0.430[[ 0.28711904]
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[[ 0.03670507 -0.1518242   0.13269105 ..., -0.15168721  0.24508471
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   0.15307815]]
Progress: 19.9% ... Training loss: 0.251 ... Validation loss: 0.427[[ 0.28550878]
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[[ 0.03622898 -0.15135341  0.13385702 ..., -0.15154003  0.24362349
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 [ 0.04593441 -0.01054134 -0.08620723 ...,  0.04218804  0.63627872
   0.15147934]]
Progress: 19.9% ... Training loss: 0.248 ... Validation loss: 0.424[[ 0.28949382]
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[[ 0.03682813 -0.15193372  0.13218104 ..., -0.15172736  0.24527088
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   0.15020931]]
Progress: 19.9% ... Training loss: 0.255 ... Validation loss: 0.433[[ 0.27755099]
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[[ 0.03556264 -0.15072054  0.13525573 ..., -0.15133912  0.24127494
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   0.15050671]]
Progress: 19.9% ... Training loss: 0.252 ... Validation loss: 0.422[[ 0.29406305]
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[[ 0.03666046 -0.1518931   0.13240508 ..., -0.15172967  0.24384604
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   0.14963058]]
Progress: 19.9% ... Training loss: 0.265 ... Validation loss: 0.445[[ 0.27596526]
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[[ 0.03555877 -0.15087557  0.13545889 ..., -0.15139549  0.24088535
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 [ 0.04589399 -0.01047317 -0.08644738 ...,  0.04219227  0.63754987
   0.15086641]]
Progress: 19.9% ... Training loss: 0.257 ... Validation loss: 0.426[[ 0.29329188]
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[[ 0.03687784 -0.15222659  0.13216325 ..., -0.15188068  0.24478434
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   0.15049863]]
Progress: 19.9% ... Training loss: 0.266 ... Validation loss: 0.450[[ 0.27469257]
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   0.15093008]]
Progress: 19.9% ... Training loss: 0.256 ... Validation loss: 0.426[[ 0.28040742]
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[[ 0.03540808 -0.15074315  0.13623665 ..., -0.15141723  0.24167901
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  -0.246012  ]
 [ 0.04612906 -0.01071291 -0.08713106 ...,  0.04211529  0.63944401
   0.15015645]]
Progress: 19.9% ... Training loss: 0.248 ... Validation loss: 0.422[[ 0.28736956]
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[[ 0.03623803 -0.15156395  0.13409953 ..., -0.15169119  0.24392435
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   0.14994957]]
Progress: 19.9% ... Training loss: 0.254 ... Validation loss: 0.427[[ 0.28037901]
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[[ 0.03629216 -0.15161665  0.13398053 ..., -0.15170806  0.24382541
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   0.15005159]]
Progress: 19.9% ... Training loss: 0.247 ... Validation loss: 0.419[[ 0.27704042]
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[[ 0.03563328 -0.15093239  0.13572949 ..., -0.15147779  0.24236431
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   0.1505858 ]]
Progress: 19.9% ... Training loss: 0.250 ... Validation loss: 0.420[[ 0.28695059]
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[[ 0.03639763 -0.1517409   0.13362734 ..., -0.1517525   0.2448262
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   0.14927269]]
Progress: 19.9% ... Training loss: 0.254 ... Validation loss: 0.426[[ 0.27308281]
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   0.15115089]]
Progress: 20.0% ... Training loss: 0.256 ... Validation loss: 0.423[[ 0.28320871]
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[[ 0.03668386 -0.15203543  0.13268364 ..., -0.15186166  0.24622102
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   0.15082156]]
Progress: 20.0% ... Training loss: 0.249 ... Validation loss: 0.421[[ 0.27776014]
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[[ 0.03632363 -0.15165146  0.1336272  ..., -0.15173117  0.24546592
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   0.1515485 ]]
Progress: 20.0% ... Training loss: 0.248 ... Validation loss: 0.416[[ 0.29022471]
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[[ 0.03707114 -0.15245864  0.13168174 ..., -0.15199649  0.2475153
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   0.15059801]]
Progress: 20.0% ... Training loss: 0.264 ... Validation loss: 0.438[[ 0.2747238 ]
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[[ 0.03659187 -0.15198165  0.13301551 ..., -0.15185972  0.24616675
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   0.15067605]]
Progress: 20.0% ... Training loss: 0.251 ... Validation loss: 0.416[[ 0.28350299]
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[[ 0.03738215 -0.15280119  0.13097324 ..., -0.15214308  0.24840497
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 [ 0.04532973 -0.00981695 -0.08543971 ...,  0.04240427  0.6413696
   0.15134345]]
Progress: 20.0% ... Training loss: 0.253 ... Validation loss: 0.417[[ 0.27493101]
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[[ 0.03659314 -0.15197684  0.13318241 ..., -0.15188958  0.2464815
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   0.15214797]]
Progress: 20.0% ... Training loss: 0.249 ... Validation loss: 0.415[[ 0.28379065]
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[[ 0.03764447 -0.15311921  0.13029247 ..., -0.15225705  0.24914077
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 [ 0.04530416 -0.0097992  -0.08540312 ...,  0.04240117  0.64141429
   0.15127147]]
Progress: 20.0% ... Training loss: 0.252 ... Validation loss: 0.421[[ 0.27414471]
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[[ 0.03665382 -0.15211312  0.13297999 ..., -0.15192762  0.24561631
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   0.15128037]]
Progress: 20.0% ... Training loss: 0.253 ... Validation loss: 0.419[[ 0.28808199]
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   0.15108499]]
Progress: 20.0% ... Training loss: 0.254 ... Validation loss: 0.430[[ 0.28031513]
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 [ 0.35196764]
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   0.15038213]]
Progress: 20.0% ... Training loss: 0.248 ... Validation loss: 0.419[[ 0.28639229]
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[[ 0.03668766 -0.15223039  0.13320389 ..., -0.15199523  0.24532623
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   0.1509919 ]]
Progress: 20.0% ... Training loss: 0.251 ... Validation loss: 0.424[[ 0.28287855]
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[[ 0.03659281 -0.15213238  0.13354517 ..., -0.15198319  0.24518927
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   0.15041046]]
Progress: 20.0% ... Training loss: 0.247 ... Validation loss: 0.417[[ 0.27870126]
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 [ 0.04582127 -0.01026013 -0.0866727  ...,  0.0422471   0.64392255
   0.14952744]]
Progress: 20.0% ... Training loss: 0.248 ... Validation loss: 0.417[[ 0.27788411]
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[[ 0.03597805 -0.1514479   0.13533934 ..., -0.15176486  0.24307642
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   0.14899474]]
Progress: 20.0% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.28191276]
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[[ 0.03584377 -0.15132468  0.13571684 ..., -0.15172158  0.24217792
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   0.14650536]]
Progress: 20.1% ... Training loss: 0.247 ... Validation loss: 0.419[[ 0.27925337]
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   0.14700975]]
Progress: 20.1% ... Training loss: 0.249 ... Validation loss: 0.419[[ 0.27616013]
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   0.14619327]]
Progress: 20.1% ... Training loss: 0.255 ... Validation loss: 0.424[[ 0.28705655]
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[[ 0.03593592 -0.1514925   0.13565592 ..., -0.15178322  0.24280894
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   0.14716673]]
Progress: 20.1% ... Training loss: 0.249 ... Validation loss: 0.424[[ 0.27135879]
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[[ 0.03473248 -0.15030149  0.13879255 ..., -0.15139399  0.23890853
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 [ 0.04610722 -0.01047205 -0.08715034 ...,  0.04216897  0.64754373
   0.14836627]]
Progress: 20.1% ... Training loss: 0.273 ... Validation loss: 0.441[[ 0.29424983]
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[[ 0.03664575 -0.15229931  0.1334332  ..., -0.15214684  0.24519721
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   0.14785937]]
Progress: 20.1% ... Training loss: 0.269 ... Validation loss: 0.448[[ 0.27115876]
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[[ 0.03510599 -0.15089916  0.13754782 ..., -0.15170602  0.24014217
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 ..., 
 [-0.18470449 -0.20489651 -0.1498121  ...,  0.09499251 -0.11801117
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 [ 0.04590213 -0.01026525 -0.08676112 ...,  0.04222451  0.64787368
   0.14883191]]
Progress: 20.1% ... Training loss: 0.281 ... Validation loss: 0.443[[ 0.2874765 ]
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[[ 0.03629952 -0.15214792  0.13415606 ..., -0.15217222  0.24418741
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   0.1475273 ]]
Progress: 20.1% ... Training loss: 0.249 ... Validation loss: 0.426[[ 0.28413636]
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[[ 0.03646671 -0.15234688  0.1336022  ..., -0.15223392  0.24455508
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Progress: 20.1% ... Training loss: 0.247 ... Validation loss: 0.419[[ 0.28410888]
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[[ 0.03719704 -0.1530947   0.13178718 ..., -0.15248875  0.24666912
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Progress: 20.1% ... Training loss: 0.247 ... Validation loss: 0.419[[ 0.28731085]
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   0.14733198]]
Progress: 20.1% ... Training loss: 0.248 ... Validation loss: 0.424[[ 0.27918183]
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 [ 0.0461938  -0.01046591 -0.0882169  ...,  0.04213788  0.65110741
   0.14755366]]
Progress: 20.1% ... Training loss: 0.249 ... Validation loss: 0.417[[ 0.2933801 ]
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   0.14610422]]
Progress: 20.1% ... Training loss: 0.263 ... Validation loss: 0.442[[ 0.27487232]
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   0.14785279]]
Progress: 20.1% ... Training loss: 0.256 ... Validation loss: 0.420[[ 0.27491305]
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   0.14682252]]
Progress: 20.1% ... Training loss: 0.254 ... Validation loss: 0.419[[ 0.28173383]
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   0.14782348]]
Progress: 20.2% ... Training loss: 0.247 ... Validation loss: 0.417[[ 0.28248823]
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   0.1465562 ]]
Progress: 20.2% ... Training loss: 0.246 ... Validation loss: 0.418[[ 0.27458685]
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[[ 0.03489519 -0.15088784  0.13771808 ..., -0.15180639  0.24029024
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   0.14773128]]
Progress: 20.2% ... Training loss: 0.252 ... Validation loss: 0.419[[ 0.29163645]
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[[ 0.03589071 -0.15193207  0.13496715 ..., -0.15216253  0.24376424
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   0.14632585]]
Progress: 20.2% ... Training loss: 0.268 ... Validation loss: 0.449[[ 0.27330262]
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[[ 0.03503837 -0.15111786  0.13706442 ..., -0.15190562  0.24060947
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   0.14695608]]
Progress: 20.2% ... Training loss: 0.256 ... Validation loss: 0.421[[ 0.29021437]
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[[ 0.03579402 -0.15192929  0.13510495 ..., -0.15218606  0.24236365
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   0.14669557]]
Progress: 20.2% ... Training loss: 0.258 ... Validation loss: 0.441[[ 0.28484237]
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[[ 0.03544955 -0.15157259  0.13599204 ..., -0.15207278  0.24101336
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   0.14598726]]
Progress: 20.2% ... Training loss: 0.248 ... Validation loss: 0.424[[ 0.27852006]
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[[ 0.03500061 -0.15116385  0.13725776 ..., -0.15193391  0.23946831
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   0.14766986]]
Progress: 20.2% ... Training loss: 0.249 ... Validation loss: 0.420[[ 0.28280303]
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Progress: 20.2% ... Training loss: 0.247 ... Validation loss: 0.422[[ 0.2803443 ]
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Progress: 20.2% ... Training loss: 0.248 ... Validation loss: 0.419[[ 0.27775643]
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   0.14534856]]
Progress: 20.2% ... Training loss: 0.251 ... Validation loss: 0.421[[ 0.29273636]
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   0.14391345]]
Progress: 20.2% ... Training loss: 0.261 ... Validation loss: 0.445[[ 0.27063422]
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   0.1461354 ]]
Progress: 20.2% ... Training loss: 0.273 ... Validation loss: 0.435[[ 0.28318028]
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Progress: 20.2% ... Training loss: 0.247 ... Validation loss: 0.423[[ 0.27091131]
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   0.14706693]]
Progress: 20.2% ... Training loss: 0.264 ... Validation loss: 0.430[[ 0.28225125]
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Progress: 20.3% ... Training loss: 0.247 ... Validation loss: 0.420[[ 0.27871405]
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Progress: 20.3% ... Training loss: 0.246 ... Validation loss: 0.418[[ 0.28166088]
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[[ 0.03471632 -0.15102588  0.138634   ..., -0.15198079  0.24027583
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   0.14669303]]
Progress: 20.3% ... Training loss: 0.247 ... Validation loss: 0.417[[ 0.27601473]
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   0.14715411]]
Progress: 20.3% ... Training loss: 0.248 ... Validation loss: 0.418[[ 0.29220233]
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   0.14548226]]
Progress: 20.3% ... Training loss: 0.281 ... Validation loss: 0.456[[ 0.27598492]
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[[ 0.0346941  -0.15111629  0.13879203 ..., -0.15208327  0.24038579
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   0.14582359]]
Progress: 20.3% ... Training loss: 0.250 ... Validation loss: 0.418[[ 0.29287256]
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[[ 0.03535704 -0.15175411  0.13695852 ..., -0.15229451  0.24279688
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   0.14437214]]
Progress: 20.3% ... Training loss: 0.283 ... Validation loss: 0.453[[ 0.26544169]
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   0.14423216]]
Progress: 20.3% ... Training loss: 0.281 ... Validation loss: 0.442[[ 0.28730114]
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Progress: 20.3% ... Training loss: 0.259 ... Validation loss: 0.428[[ 0.27025742]
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   0.1456353 ]]
Progress: 20.3% ... Training loss: 0.261 ... Validation loss: 0.425[[ 0.28038182]
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   0.14585117]]
Progress: 20.3% ... Training loss: 0.246 ... Validation loss: 0.415[[ 0.27422802]
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   0.1464299 ]]
Progress: 20.3% ... Training loss: 0.252 ... Validation loss: 0.418[[ 0.2855193 ]
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   0.14554696]]
Progress: 20.3% ... Training loss: 0.250 ... Validation loss: 0.424[[ 0.276509  ]
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   0.14574043]]
Progress: 20.3% ... Training loss: 0.251 ... Validation loss: 0.417[[ 0.27565661]
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   0.14523045]]
Progress: 20.3% ... Training loss: 0.252 ... Validation loss: 0.418[[ 0.2820155 ]
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Progress: 20.4% ... Training loss: 0.245 ... Validation loss: 0.417[[ 0.28139466]
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   0.14467933]]
Progress: 20.4% ... Training loss: 0.246 ... Validation loss: 0.417[[ 0.27871764]
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   0.14436582]]
Progress: 20.4% ... Training loss: 0.246 ... Validation loss: 0.415[[ 0.28739974]
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[[ 0.03518729 -0.15192543  0.13716841 ..., -0.15252545  0.2447359
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   0.14401951]]
Progress: 20.4% ... Training loss: 0.255 ... Validation loss: 0.429[[ 0.27570029]
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[[ 0.03467657 -0.15144821  0.13845727 ..., -0.15237845  0.24297347
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   0.14294939]]
Progress: 20.4% ... Training loss: 0.250 ... Validation loss: 0.415[[ 0.27260725]
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[[ 0.03421022 -0.15096563  0.1399155  ..., -0.15220374  0.24137764
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   0.14376851]]
Progress: 20.4% ... Training loss: 0.258 ... Validation loss: 0.422[[ 0.28456091]
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   0.14416652]]
Progress: 20.4% ... Training loss: 0.247 ... Validation loss: 0.424[[ 0.28152239]
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[[ 0.03452323 -0.15133462  0.13898077 ..., -0.15232044  0.24221717
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   0.14389412]]
Progress: 20.4% ... Training loss: 0.245 ... Validation loss: 0.418[[ 0.27753469]
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[[ 0.03475329 -0.15155384  0.13844458 ..., -0.15239402  0.24321384
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   0.14450165]]
Progress: 20.4% ... Training loss: 0.246 ... Validation loss: 0.415[[ 0.28441792]
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Progress: 20.4% ... Training loss: 0.249 ... Validation loss: 0.422[[ 0.28298609]
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   0.14299039]]
Progress: 20.4% ... Training loss: 0.249 ... Validation loss: 0.419[[ 0.26506551]
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   0.14415674]]
Progress: 20.4% ... Training loss: 0.274 ... Validation loss: 0.429[[ 0.28653721]
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Progress: 20.4% ... Training loss: 0.258 ... Validation loss: 0.433[[ 0.2758598 ]
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Progress: 20.4% ... Training loss: 0.246 ... Validation loss: 0.412[[ 0.28189296]
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   0.14242452]]
Progress: 20.4% ... Training loss: 0.247 ... Validation loss: 0.415[[ 0.28070568]
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   0.14406299]]
Progress: 20.5% ... Training loss: 0.245 ... Validation loss: 0.415[[ 0.28876969]
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[[ 0.0351278  -0.15204525  0.13757268 ..., -0.15262602  0.24542022
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 [ 0.04732992 -0.01137494 -0.09275371 ...,  0.04172383  0.67297096
   0.14208892]]
Progress: 20.5% ... Training loss: 0.259 ... Validation loss: 0.431[[ 0.27478766]
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[[ 0.03433289 -0.1513067   0.13973493 ..., -0.15240078  0.2431059
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 [ 0.04720625 -0.01124747 -0.0924112  ...,  0.0417611   0.6730092
   0.14237766]]
Progress: 20.5% ... Training loss: 0.252 ... Validation loss: 0.415[[ 0.28451653]
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[[ 0.03459884 -0.15155601  0.13924054 ..., -0.15247307  0.24443416
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   0.14125185]]
Progress: 20.5% ... Training loss: 0.248 ... Validation loss: 0.418[[ 0.28018106]
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[[ 0.03431231 -0.15127841  0.13997806 ..., -0.15238956  0.24364506
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   0.14222766]]
Progress: 20.5% ... Training loss: 0.245 ... Validation loss: 0.414[[ 0.27670156]
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[[ 0.03438336 -0.15129373  0.1398656  ..., -0.15239651  0.24423441
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   0.14282026]]
Progress: 20.5% ... Training loss: 0.246 ... Validation loss: 0.414[[ 0.26905058]
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[[ 0.03315257 -0.14998373  0.14352792 ..., -0.15198742  0.24127766
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   0.14357327]]
Progress: 20.5% ... Training loss: 0.261 ... Validation loss: 0.422[[ 0.28970231]
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[[ 0.03451635 -0.15149864  0.13961068 ..., -0.15246125  0.24560488
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   0.14240339]]
Progress: 20.5% ... Training loss: 0.265 ... Validation loss: 0.444[[ 0.28009763]
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[[ 0.03429426 -0.15128777  0.14018862 ..., -0.15240452  0.24505319
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 [ 0.04640672 -0.01038184 -0.09048388 ...,  0.04201093  0.67316931
   0.14366913]]
Progress: 20.5% ... Training loss: 0.246 ... Validation loss: 0.417[[ 0.26325943]
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[[ 0.03351067 -0.15051273  0.14246288 ..., -0.15216077  0.24210637
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   0.14402646]]
Progress: 20.5% ... Training loss: 0.290 ... Validation loss: 0.442[[ 0.28316316]
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[[ 0.03456065 -0.15169421  0.13920958 ..., -0.15255617  0.24545565
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   0.14303479]]
Progress: 20.5% ... Training loss: 0.247 ... Validation loss: 0.423[[ 0.28068608]
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[[ 0.03439716 -0.15151432  0.1397484  ..., -0.15251072  0.24496738
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   0.14278492]]
Progress: 20.5% ... Training loss: 0.246 ... Validation loss: 0.418[[ 0.28030262]
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[[ 0.03451234 -0.1516039   0.13948346 ..., -0.15254285  0.24524655
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   0.14224688]]
Progress: 20.5% ... Training loss: 0.246 ... Validation loss: 0.419[[ 0.27113599]
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[[ 0.03388038 -0.15098445  0.14150293 ..., -0.15234904  0.24334929
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   0.14355961]]
Progress: 20.5% ... Training loss: 0.255 ... Validation loss: 0.417[[ 0.2771272 ]
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[[ 0.0341014  -0.15118431  0.14098257 ..., -0.15241332  0.24443757
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   0.14333589]]
Progress: 20.5% ... Training loss: 0.246 ... Validation loss: 0.416[[ 0.27978598]
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[[ 0.03424233 -0.15134034  0.1408121  ..., -0.15244873  0.244313
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   0.14356006]]
Progress: 20.6% ... Training loss: 0.246 ... Validation loss: 0.422[[ 0.28814474]
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[[ 0.0352284  -0.1523572   0.13815918 ..., -0.15276168  0.2476921
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   0.1443395 ]]
Progress: 20.6% ... Training loss: 0.263 ... Validation loss: 0.448[[ 0.272344  ]
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[[ 0.03366081 -0.15085304  0.14207804 ..., -0.15230506  0.24326105
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   0.14535483]]
Progress: 20.6% ... Training loss: 0.253 ... Validation loss: 0.416[[ 0.28414751]
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[[ 0.0336744  -0.15081747  0.14221098 ..., -0.15230129  0.24375854
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 [ 0.04611285 -0.0100235  -0.09004028 ...,  0.04210661  0.67618     0.14348463]]
Progress: 20.6% ... Training loss: 0.253 ... Validation loss: 0.432[[ 0.27019554]
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[[ 0.0329983  -0.15016175  0.14394235 ..., -0.15209232  0.24162634
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   0.14469718]]
Progress: 20.6% ... Training loss: 0.252 ... Validation loss: 0.416[[ 0.28860697]
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[[ 0.03385688 -0.15108364  0.1415944  ..., -0.1523845   0.24428594
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   0.14340822]]
Progress: 20.6% ... Training loss: 0.268 ... Validation loss: 0.448[[ 0.27945896]
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[[ 0.0332975  -0.15055324  0.14296157 ..., -0.15222258  0.24225915
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   0.14455568]]
Progress: 20.6% ... Training loss: 0.246 ... Validation loss: 0.416[[ 0.28064014]
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   0.14514082]]
Progress: 20.6% ... Training loss: 0.248 ... Validation loss: 0.418[[ 0.26532941]
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   0.14617961]]
Progress: 20.6% ... Training loss: 0.271 ... Validation loss: 0.429[[ 0.27417948]
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   0.14494956]]
Progress: 20.6% ... Training loss: 0.248 ... Validation loss: 0.414[[ 0.28018701]
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[[ 0.03318328 -0.15052044  0.14354876 ..., -0.15223828  0.24186157
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   0.14562004]]
Progress: 20.6% ... Training loss: 0.245 ... Validation loss: 0.421[[ 0.28346524]
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[[ 0.03361301 -0.15096916  0.14239493 ..., -0.15237438  0.24341406
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   0.14498821]]
Progress: 20.6% ... Training loss: 0.248 ... Validation loss: 0.425[[ 0.27828003]
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[[ 0.0333694  -0.15075237  0.1431385  ..., -0.15230347  0.24275027
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   0.14624963]]
Progress: 20.6% ... Training loss: 0.245 ... Validation loss: 0.415[[ 0.28010922]
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[[ 0.03356837 -0.15091678  0.14277933 ..., -0.15236124  0.24337436
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   0.14601898]]
Progress: 20.6% ... Training loss: 0.246 ... Validation loss: 0.418[[ 0.27469126]
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   0.14539099]]
Progress: 20.6% ... Training loss: 0.246 ... Validation loss: 0.412[[ 0.29306442]
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   0.14442141]]
Progress: 20.7% ... Training loss: 0.287 ... Validation loss: 0.474[[ 0.27991758]
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[[ 0.03389022 -0.15127343  0.1421451  ..., -0.15248944  0.24391457
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   0.14443017]]
Progress: 20.7% ... Training loss: 0.247 ... Validation loss: 0.420[[ 0.27630353]
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[[ 0.03340781 -0.15080578  0.14344284 ..., -0.15234908  0.24205248
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   0.14425335]]
Progress: 20.7% ... Training loss: 0.245 ... Validation loss: 0.414[[ 0.28228951]
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[[ 0.03441914 -0.15187003  0.14070823 ..., -0.15268367  0.24517215
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   0.14352746]]
Progress: 20.7% ... Training loss: 0.248 ... Validation loss: 0.429[[ 0.26947505]
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[[ 0.03364289 -0.1510788   0.1428666  ..., -0.15245061  0.24288977
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   0.14418233]]
Progress: 20.7% ... Training loss: 0.254 ... Validation loss: 0.413[[ 0.27881045]
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[[ 0.03398503 -0.1514154   0.14204307 ..., -0.15256274  0.24393755
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   0.14324822]]
Progress: 20.7% ... Training loss: 0.246 ... Validation loss: 0.422[[ 0.27397356]
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[[ 0.03417899 -0.15161851  0.14160275 ..., -0.1526171   0.24433684
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   0.14384374]]
Progress: 20.7% ... Training loss: 0.245 ... Validation loss: 0.414[[ 0.27023262]
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[[ 0.03379189 -0.15119908  0.14282906 ..., -0.15249478  0.24333215
  -0.10961105]
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   0.14291715]]
Progress: 20.7% ... Training loss: 0.249 ... Validation loss: 0.412[[ 0.28224083]
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[[ 0.03445856 -0.15189237  0.14101197 ..., -0.15272202  0.2451385
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   0.14091606]]
Progress: 20.7% ... Training loss: 0.254 ... Validation loss: 0.435[[ 0.27256187]
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[[ 0.03412387 -0.1515747   0.14185082 ..., -0.15263055  0.24370499
  -0.11055556]
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  -0.24498828]
 [ 0.04626054 -0.01014137 -0.09172922 ...,  0.0419929   0.68378093
   0.14079035]]
Progress: 20.7% ... Training loss: 0.246 ... Validation loss: 0.412[[ 0.26764657]
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[[ 0.03434509 -0.1517964   0.14122625 ..., -0.15270011  0.24472972
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 [ 0.04591691 -0.00976577 -0.09088726 ...,  0.04211034  0.68315267
   0.14149181]]
Progress: 20.7% ... Training loss: 0.249 ... Validation loss: 0.411[[ 0.27156655]
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[[ 0.03433906 -0.15178923  0.14132264 ..., -0.15268849  0.24524568
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 [ 0.04591366 -0.00974851 -0.09087602 ...,  0.04211301  0.68391113
   0.1413139 ]]
Progress: 20.7% ... Training loss: 0.244 ... Validation loss: 0.410[[ 0.27605436]
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[[ 0.03459017 -0.1520482   0.14050058 ..., -0.15276466  0.24599509
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 [ 0.04600087 -0.00983269 -0.0911297  ...,  0.04208358  0.68451517
   0.14106335]]
Progress: 20.7% ... Training loss: 0.246 ... Validation loss: 0.417[[ 0.26933438]
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[[ 0.03426614 -0.15170541  0.1413523  ..., -0.15266455  0.2451336
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   0.14061979]]
Progress: 20.7% ... Training loss: 0.246 ... Validation loss: 0.410[[ 0.27312108]
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[[ 0.03435787 -0.15177384  0.14127223 ..., -0.15270118  0.24578817
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 [ 0.04632287 -0.0101701  -0.09194206 ...,  0.04198261  0.6860641
   0.14001843]]
Progress: 20.7% ... Training loss: 0.244 ... Validation loss: 0.411[[ 0.2746198 ]
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[[ 0.03430512 -0.15168723  0.14133222 ..., -0.15265861  0.2456963
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 [ 0.0464547  -0.01029941 -0.09237057 ...,  0.0419392   0.68667654
   0.13952222]]
Progress: 20.8% ... Training loss: 0.246 ... Validation loss: 0.413[[ 0.27367262]
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[[ 0.03450371 -0.15188842  0.14077655 ..., -0.15271074  0.24612129
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   0.13911565]]
Progress: 20.8% ... Training loss: 0.245 ... Validation loss: 0.412[[ 0.26391587]
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[[ 0.03402261 -0.15133733  0.14220899 ..., -0.15254406  0.24505547
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   0.13870735]]
Progress: 20.8% ... Training loss: 0.253 ... Validation loss: 0.414[[ 0.27926662]
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[[ 0.03452147 -0.15184803  0.14102312 ..., -0.15273942  0.24719286
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 [ 0.04708245 -0.01094555 -0.09424852 ...,  0.04172263  0.68900227
   0.13736768]]
Progress: 20.8% ... Training loss: 0.259 ... Validation loss: 0.433[[ 0.26627798]
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[[ 0.03406843 -0.15141349  0.1422982  ..., -0.15260847  0.24525935
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 [ 0.04743518 -0.01129388 -0.09518404 ...,  0.04161564  0.689866
   0.13637941]]
Progress: 20.8% ... Training loss: 0.248 ... Validation loss: 0.412[[ 0.27210799]
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[[ 0.03471948 -0.15212701  0.14039684 ..., -0.15281464  0.24819011
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 [ 0.04720918 -0.01103664 -0.09460288 ...,  0.0417      0.68952445
   0.13706132]]
Progress: 20.8% ... Training loss: 0.245 ... Validation loss: 0.415[[ 0.26529583]
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[[ 0.03431558 -0.151642    0.14150668 ..., -0.15269536  0.2478608
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   0.13846483]]
Progress: 20.8% ... Training loss: 0.249 ... Validation loss: 0.412[[ 0.28137654]
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   0.136188  ]]
Progress: 20.8% ... Training loss: 0.270 ... Validation loss: 0.441[[ 0.26706229]
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[[ 0.03525967 -0.15269748  0.13887431 ..., -0.15305409  0.25094984
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   0.13805209]]
Progress: 20.8% ... Training loss: 0.246 ... Validation loss: 0.409[[ 0.27104771]
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   0.13778806]]
Progress: 20.8% ... Training loss: 0.245 ... Validation loss: 0.411[[ 0.26536874]
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   0.13777254]]
Progress: 20.8% ... Training loss: 0.249 ... Validation loss: 0.413[[ 0.28201073]
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   0.13421714]]
Progress: 20.8% ... Training loss: 0.264 ... Validation loss: 0.438[[ 0.26448685]
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[[ 0.03415748 -0.15160795  0.14185751 ..., -0.15275159  0.24684475
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   0.13427292]]
Progress: 20.8% ... Training loss: 0.253 ... Validation loss: 0.417[[ 0.26632955]
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   0.13406741]]
Progress: 20.8% ... Training loss: 0.249 ... Validation loss: 0.415[[ 0.27406922]
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   0.13412311]]
Progress: 20.8% ... Training loss: 0.245 ... Validation loss: 0.418[[ 0.27765785]
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[[ 0.03462831 -0.15201045  0.14102032 ..., -0.15288952  0.24848687
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   0.13342564]]
Progress: 20.9% ... Training loss: 0.251 ... Validation loss: 0.427[[ 0.27911781]
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[[ 0.03465877 -0.15203352  0.14108963 ..., -0.15288101  0.24873222
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   0.13310132]]
Progress: 20.9% ... Training loss: 0.256 ... Validation loss: 0.430[[ 0.2677466 ]
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   0.13297561]]
Progress: 20.9% ... Training loss: 0.245 ... Validation loss: 0.409[[ 0.27467285]
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[[ 0.03394352 -0.15131842  0.14314258 ..., -0.15268624  0.24676099
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   0.13231457]]
Progress: 20.9% ... Training loss: 0.247 ... Validation loss: 0.414[[ 0.27158956]
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[[ 0.03405062 -0.15144321  0.14300869 ..., -0.1527215   0.24691502
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   0.13308227]]
Progress: 20.9% ... Training loss: 0.244 ... Validation loss: 0.411[[ 0.28057322]
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[[ 0.03461965 -0.15208214  0.14160143 ..., -0.15293717  0.24857372
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 [ 0.0449438   0.04217348  0.08292234 ..., -0.24727051  0.03011832
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   0.13254415]]
Progress: 20.9% ... Training loss: 0.256 ... Validation loss: 0.429[[ 0.27325449]
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[[ 0.03410748 -0.15158626  0.14315507 ..., -0.15276903  0.24771782
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   0.13337193]]
Progress: 20.9% ... Training loss: 0.244 ... Validation loss: 0.413[[ 0.26338409]
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   0.13219459]]
Progress: 20.9% ... Training loss: 0.256 ... Validation loss: 0.415[[ 0.28264199]
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   0.13070917]]
Progress: 20.9% ... Training loss: 0.271 ... Validation loss: 0.449[[  2.57078116e-01]
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[[ 0.03296473 -0.15060895  0.14635411 ..., -0.1525329   0.24495556
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   0.13254214]]
Progress: 20.9% ... Training loss: 0.277 ... Validation loss: 0.432[[ 0.27873254]
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[[ 0.03423933 -0.1520371   0.1425089  ..., -0.15300638  0.24933146
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   0.1310196 ]]
Progress: 20.9% ... Training loss: 0.255 ... Validation loss: 0.425[[  2.57186427e-01]
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   0.13236323]]
Progress: 20.9% ... Training loss: 0.272 ... Validation loss: 0.425[[ 0.27987514]
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Progress: 20.9% ... Training loss: 0.261 ... Validation loss: 0.430[[  2.55500575e-01]
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[[ 0.03260868 -0.15056919  0.1466869  ..., -0.15259397  0.24470547
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Progress: 20.9% ... Training loss: 0.279 ... Validation loss: 0.436[[ 0.27822437]
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[[ 0.03346989 -0.15154432  0.14426676 ..., -0.1529186   0.24792281
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Progress: 20.9% ... Training loss: 0.256 ... Validation loss: 0.427[[ 0.2669972 ]
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[[ 0.03312322 -0.15116511  0.14526542 ..., -0.15281311  0.24744684
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   0.13235651]]
Progress: 21.0% ... Training loss: 0.244 ... Validation loss: 0.406[[ 0.2694745 ]
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Progress: 21.0% ... Training loss: 0.244 ... Validation loss: 0.407[[ 0.26877959]
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   0.13259562]]
Progress: 21.0% ... Training loss: 0.243 ... Validation loss: 0.408[[ 0.27039841]
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   0.13231787]]
Progress: 21.0% ... Training loss: 0.244 ... Validation loss: 0.410[[ 0.26336159]
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Progress: 21.0% ... Training loss: 0.250 ... Validation loss: 0.412[[ 0.27691501]
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   0.13309882]]
Progress: 21.0% ... Training loss: 0.254 ... Validation loss: 0.424[[ 0.28016617]
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   0.13366831]]
Progress: 21.0% ... Training loss: 0.260 ... Validation loss: 0.433[[ 0.26373347]
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[[ 0.03312575 -0.15130657  0.14582137 ..., -0.15288122  0.24530726
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   0.13450883]]
Progress: 21.0% ... Training loss: 0.252 ... Validation loss: 0.415[[ 0.273306  ]
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[[ 0.03401982 -0.15224341  0.14343043 ..., -0.15320557  0.24903085
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 [ 0.04665619 -0.01054384 -0.094758   ...,  0.04169155  0.70121348
   0.13520023]]
Progress: 21.0% ... Training loss: 0.246 ... Validation loss: 0.413[[ 0.26370722]
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[[ 0.03311109 -0.15129955  0.14580994 ..., -0.15294287  0.2464182
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 [ 0.04639031 -0.01026152 -0.09413092 ...,  0.04176684  0.70079528
   0.13573507]]
Progress: 21.0% ... Training loss: 0.249 ... Validation loss: 0.413[[ 0.2682504 ]
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[[ 0.03310855 -0.15130533  0.14587773 ..., -0.15293653  0.2463099
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   0.13528009]]
Progress: 21.0% ... Training loss: 0.244 ... Validation loss: 0.410[[ 0.27489612]
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[[ 0.03303186 -0.15123524  0.14609622 ..., -0.15289106  0.24651962
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   0.13534204]]
Progress: 21.0% ... Training loss: 0.248 ... Validation loss: 0.415[[ 0.27319295]
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[[ 0.0331609  -0.15135382  0.14583816 ..., -0.15292111  0.24717307
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   0.13625553]]
Progress: 21.0% ... Training loss: 0.245 ... Validation loss: 0.413[[ 0.2691007 ]
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Progress: 76.6% ... Training loss: 0.067 ... Validation loss: 0.149[[-0.16868546]
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[[-0.01751606 -0.30205771  0.2677551  ..., -0.23124259 -0.35488729
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Progress: 76.6% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16463476]
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[[-0.01774438 -0.30335931  0.26684492 ..., -0.23163546 -0.35312794
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  -0.06312762]]
Progress: 76.6% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16800382]
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[[-0.01757488 -0.30240764  0.26798408 ..., -0.23133113 -0.3556999
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  -0.06331487]]
Progress: 76.6% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16872501]
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  -0.06273866]]
Progress: 76.6% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16442559]
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[[-0.01782058 -0.30371017  0.26643441 ..., -0.23176659 -0.35186386
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  -0.06301399]]
Progress: 76.6% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.1707116 ]
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  -0.06274023]]
Progress: 76.6% ... Training loss: 0.066 ... Validation loss: 0.141[[-0.16275579]
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  -0.06392787]]
Progress: 76.7% ... Training loss: 0.065 ... Validation loss: 0.142[[-0.16467026]
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[[-0.01772837 -0.30303746  0.26747536 ..., -0.23155996 -0.35421791
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 [ 0.03893944  0.08396831 -0.04487878 ...,  0.05352914  2.88935244
  -0.06391756]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.1666212 ]
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 [ 0.03906592  0.08471107 -0.04402621 ...,  0.05375277  2.88923418
  -0.06300523]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16439223]
 [-0.95022176]
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[[-0.01788282 -0.30388838  0.26658913 ..., -0.23181865 -0.35101974
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  -0.33217952]
 [ 0.0390029   0.08432388 -0.04422951 ...,  0.05364627  2.88946581
  -0.06332347]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.1766748 ]
 [-0.96091423]
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[[-0.01753068 -0.30192251  0.26900796 ..., -0.23118293 -0.35479755
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  -0.33071878]
 [ 0.03927887  0.08586661 -0.04272185 ...,  0.05414957  2.88916606
  -0.06105249]]
Progress: 76.7% ... Training loss: 0.086 ... Validation loss: 0.156[[-0.15971674]
 [-0.94667201]
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[[-0.01819797 -0.30543691  0.26545435 ..., -0.23230681 -0.34694185
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  -0.33066694]
 [ 0.03895729  0.0841307  -0.04433247 ...,  0.05359708  2.88958345
  -0.0632314 ]]
Progress: 76.7% ... Training loss: 0.068 ... Validation loss: 0.155[[-0.16651517]
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[[-0.01796072 -0.30410005  0.26636878 ..., -0.23186436 -0.351795
   0.25396576]
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 [-0.18521623 -0.2436256  -0.376557   ...,  0.08831945 -0.60315864
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 [ 0.03903488  0.08457136 -0.04388931 ...,  0.05374235  2.88937274
  -0.06248833]]
Progress: 76.7% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16316119]
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[[-0.01798557 -0.3042529   0.26597708 ..., -0.23190658 -0.35127108
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 [ 0.03893704  0.08401628 -0.04465603 ...,  0.05355889  2.88941802
  -0.06321616]]
Progress: 76.7% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.1662886 ]
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[[-0.01789742 -0.3037798   0.26648434 ..., -0.23173977 -0.35203098
   0.25448977]
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 [ 0.03896356  0.08416099 -0.04448363 ...,  0.0536064   2.88929834
  -0.06306554]]
Progress: 76.7% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16472636]
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[[-0.01814025 -0.30517855  0.26486639 ..., -0.23218123 -0.34717371
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 ..., 
 [-0.18520915 -0.24363037 -0.37683083 ...,  0.08833284 -0.60280688
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 [ 0.03892244  0.08388977 -0.04460498 ...,  0.05352018  2.88935177
  -0.06335637]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16791864]
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[[-0.01794505 -0.30413034  0.26577986 ..., -0.23183934 -0.34994768
   0.25336648]
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 ..., 
 [-0.18520939 -0.24363854 -0.37690118 ...,  0.08832739 -0.60254313
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  -0.33088279]
 [ 0.03901222  0.08440561 -0.04443177 ...,  0.05368362  2.88924784
  -0.06294807]]
Progress: 76.7% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.1617595 ]
 [-0.94720862]
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[[-0.0181907  -0.30552562  0.26467683 ..., -0.23228849 -0.34579434
   0.25091964]
 [ 0.05876192  0.14771777  0.00636598 ..., -0.2215778   1.56603331
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 [-0.18519242 -0.24357616 -0.37678626 ...,  0.08835401 -0.60271454
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 [ 0.03888991  0.08370542 -0.04515551 ...,  0.05345757  2.8892947
  -0.06364026]]
Progress: 76.7% ... Training loss: 0.066 ... Validation loss: 0.148[[-0.16785435]
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[[-0.0179903  -0.30442253  0.26553478 ..., -0.23194359 -0.35078989
   0.25225798]
 [ 0.05874441  0.14761822  0.00626872 ..., -0.22160708  1.56610902
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 ..., 
 [-0.18500622 -0.2425729  -0.37592063 ...,  0.08869313 -0.60477191
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 [ 0.03893437  0.08396786 -0.04500142 ...,  0.0535356   2.88943102
  -0.06365824]]
Progress: 76.7% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16740523]
 [-0.95330721]
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[[-0.01810987 -0.30495398  0.265047   ..., -0.23215793 -0.34569178
   0.25175137]
 [ 0.05867934  0.14728935  0.00608825 ..., -0.22172372  1.56666254
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 ..., 
 [-0.18499737 -0.24256268 -0.37599689 ...,  0.08870362 -0.60487004
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 [ 0.03910393  0.08489779 -0.04423611 ...,  0.05383893  2.88930138
  -0.06238741]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16509261]
 [-0.95067016]
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[[-0.01810691 -0.30491089  0.26494156 ..., -0.23214766 -0.34853566
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 [ 0.05864944  0.14712744  0.00603379 ..., -0.2217769   1.56685477
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 [-0.18497248 -0.24244764 -0.37584841 ...,  0.08873701 -0.60558993
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 [ 0.03907853  0.08477071 -0.0443945  ...,  0.05379571  2.88933593
  -0.06238295]]
Progress: 76.7% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16651132]
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 [ 0.38316141]
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 [ 4.27194754]
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[[-0.01801006 -0.30435432  0.26520538 ..., -0.23194868 -0.35039598
   0.25277738]
 [ 0.05863446  0.1470328   0.00579796 ..., -0.22180523  1.56651191
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 [-0.18487161 -0.2418732  -0.37545972 ...,  0.0889122  -0.60674965
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  -0.33131553]
 [ 0.03906681  0.08470972 -0.04450365 ...,  0.05377142  2.88939841
  -0.06264911]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16219889]
 [-0.94805586]
 [-1.17677768]
 [-0.76911665]
 [-0.05352725]
 [ 2.58684336]
 [-0.04823853]
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 [ 1.00356587]
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 [ 4.27858563]
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[[-0.01825571 -0.30573241  0.26358345 ..., -0.23239187 -0.34513368
   0.25037451]
 [ 0.05866929  0.14720965  0.00601722 ..., -0.22174186  1.56651648
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 [-0.1850234  -0.24269171 -0.37638541 ...,  0.08864854 -0.60397102
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  -0.33202211]
 [ 0.03905982  0.08471759 -0.0448602  ...,  0.053762    2.88957701
  -0.06306951]]
Progress: 76.8% ... Training loss: 0.065 ... Validation loss: 0.144[[-0.16946261]
 [-0.95365957]
 [-1.18123094]
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 [-0.05862869]
 [ 2.58120522]
 [-0.05496108]
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[[-0.01785856 -0.3034538   0.26585493 ..., -0.231666   -0.34989214
   0.25419153]
 [ 0.05861948  0.14692872  0.00568369 ..., -0.2218307   1.56648236
   0.11492883]
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 ..., 
 [-0.1849502  -0.24229288 -0.37614635 ...,  0.08878527 -0.60562123
  -0.31703092]
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  -0.33145803]
 [ 0.0391858   0.08542561 -0.04408951 ...,  0.05398494  2.88941814
  -0.06207237]]
Progress: 76.8% ... Training loss: 0.064 ... Validation loss: 0.139[[-0.16747873]
 [-0.95123399]
 [-1.17852781]
 [-0.77462609]
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 [ 2.58404406]
 [-0.05269202]
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 [ 0.14236233]
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[[-0.01804281 -0.3044949   0.26457562 ..., -0.23198006 -0.34816047
   0.25238647]
 [ 0.0586053   0.14685297  0.005616   ..., -0.22185166  1.56661837
   0.11478339]
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   0.96186746]
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 [-0.18487187 -0.24186093 -0.37575615 ...,  0.08892822 -0.60699219
  -0.3164936 ]
 [-0.27585212 -0.18476601 -0.18326428 ..., -0.11870694 -0.15712263
  -0.33189462]
 [ 0.03921563  0.08560539 -0.04387046 ...,  0.05404734  2.88955663
  -0.06223051]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16267486]
 [-0.9479301 ]
 [-1.17652321]
 [-0.77114556]
 [-0.05382027]
 [ 2.58827991]
 [-0.04841336]
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 [ 1.00610533]
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 [ 0.14657354]
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[[-0.01817673 -0.30519637  0.26380067 ..., -0.23220125 -0.34517709
   0.25184378]
 [ 0.05858691  0.1467505   0.00560621 ..., -0.22188431  1.56663835
   0.11463428]
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   0.95892241]
 ..., 
 [-0.18492045 -0.24211143 -0.37612116 ...,  0.08884962 -0.6062609
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  -0.33268743]
 [ 0.03912451  0.08507289 -0.0442937  ...,  0.05387561  2.88962358
  -0.06279387]]
Progress: 76.8% ... Training loss: 0.066 ... Validation loss: 0.142[[-0.1695868 ]
 [-0.95368867]
 [-1.18174111]
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 [-0.05884894]
 [ 2.58406594]
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[[-0.01802221 -0.30436327  0.26464527 ..., -0.23193477 -0.34751395
   0.25348933]
 [ 0.05865273  0.14712264  0.00589168 ..., -0.2217636   1.56629331
   0.11515562]
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 ..., 
 [-0.1848832  -0.24192771 -0.3759551  ...,  0.08891995 -0.60708795
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  -0.33277378]
 [ 0.03922103  0.08564261 -0.04373303 ...,  0.05405306  2.88951897
  -0.06183942]]
Progress: 76.8% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16960649]
 [-0.95338936]
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 [-0.77649626]
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 [ 2.58327126]
 [-0.05487427]
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[[-0.01809036 -0.30468808  0.26423531 ..., -0.23205214 -0.34698576
   0.25303498]
 [ 0.05863049  0.14700689  0.00578882 ..., -0.22180176  1.56647103
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 ..., 
 [-0.18492546 -0.24216066 -0.37641517 ...,  0.08885608 -0.60688925
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  -0.33212511]
 [ 0.03917251  0.0853587  -0.04393665 ...,  0.05396714  2.8898561
  -0.06242257]]
Progress: 76.8% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.1686852 ]
 [-0.95299275]
 [-1.18072411]
 [-0.77558526]
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 [ 2.58312888]
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[[-0.01817044 -0.30509158  0.26360843 ..., -0.23216429 -0.34523543
   0.25276626]
 [ 0.05856356  0.14663168  0.00532145 ..., -0.22191267  1.56656666
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 ..., 
 [-0.18493996 -0.24222655 -0.37641462 ...,  0.08883203 -0.6062634
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 [-0.27583051 -0.18474705 -0.18308325 ..., -0.11868565 -0.15645283
  -0.33232972]
 [ 0.03919428  0.08548132 -0.0439372  ...,  0.05400221  2.88974434
  -0.06241125]]
Progress: 76.8% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16923978]
 [-0.95388215]
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[[-0.01809921 -0.30463712  0.26403615 ..., -0.23205744 -0.34521971
   0.25335572]
 [ 0.05861678  0.14693167  0.00556163 ..., -0.22183281  1.56645237
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 ..., 
 [-0.18492156 -0.24211756 -0.37628984 ...,  0.08886646 -0.60699846
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  -0.33207038]
 [ 0.0392283   0.08568509 -0.04372551 ...,  0.05405825  2.88964912
  -0.06187286]]
Progress: 76.8% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.1662163 ]
 [-0.95112006]
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[[-0.01811368 -0.30466716  0.26383158 ..., -0.23207699 -0.34383969
   0.25405664]
 [ 0.0584945   0.14628536  0.00472047 ..., -0.22204517  1.56699661
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 ..., 
 [-0.1848496  -0.24168962 -0.37604215 ...,  0.08899773 -0.60827733
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 [-0.27583326 -0.18475927 -0.18313214 ..., -0.11869212 -0.15704532
  -0.33241312]
 [ 0.03925508  0.08584456 -0.0434964  ...,  0.05410602  2.88958635
  -0.06159891]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16880268]
 [-0.95333609]
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 [ 2.57837101]
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[[-0.01789773 -0.3034094   0.26512184 ..., -0.23170374 -0.34662406
   0.25629706]
 [ 0.05851171  0.14637595  0.00476128 ..., -0.22201662  1.56692056
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   0.96646334]
 ..., 
 [-0.18486248 -0.24177255 -0.37605115 ...,  0.0889722  -0.60807964
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 [-0.27581752 -0.18467298 -0.18298332 ..., -0.1186689  -0.15709099
  -0.33229155]
 [ 0.03921679  0.08562497 -0.04371115 ...,  0.05402841  2.88960885
  -0.06176255]]
Progress: 76.8% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16666097]
 [-0.95151487]
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 [-0.05644509]
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[[-0.01807203 -0.30438083  0.26399105 ..., -0.23202234 -0.34561163
   0.25431851]
 [ 0.05844708  0.14600917  0.00433741 ..., -0.22213018  1.56743482
   0.11287202]
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 ..., 
 [-0.1848881  -0.24194158 -0.37608767 ...,  0.08892095 -0.60793785
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 [-0.27579136 -0.18454046 -0.18276494 ..., -0.11862228 -0.15693946
  -0.3320341 ]
 [ 0.03913268  0.08514616 -0.04419366 ...,  0.05386973  2.88972915
  -0.0622657 ]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16645184]
 [-0.95191295]
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[[-0.01816264 -0.30488882  0.26374123 ..., -0.23218635 -0.34355846
   0.25349845]
 [ 0.05844711  0.14600712  0.00431239 ..., -0.222131    1.56743547
   0.1127982 ]
 [-0.0625815   0.25186974  0.46538713 ...,  0.23107024 -0.32066334
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 ..., 
 [-0.18490814 -0.24208041 -0.37650721 ...,  0.08887874 -0.60724992
  -0.31664482]
 [-0.27586343 -0.18492524 -0.18296099 ..., -0.11874207 -0.15586466
  -0.33270125]
 [ 0.03912212  0.08507607 -0.04428563 ...,  0.05384576  2.88979393
  -0.06261142]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16972205]
 [-0.95445179]
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 [-0.77673079]
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 [ 2.58059786]
 [-0.05581984]
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 [ 1.00312778]
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[[-0.01804497 -0.30427903  0.26390703 ..., -0.23197328 -0.34453936
   0.25386713]
 [ 0.05842808  0.14591328  0.00417776 ..., -0.22216493  1.56750951
   0.11259092]
 [-0.06253624  0.25206582  0.46589448 ...,  0.2311379  -0.32172027
   0.9630134 ]
 ..., 
 [-0.18487526 -0.24189051 -0.37645573 ...,  0.08893121 -0.60695853
  -0.31649609]
 [-0.27570177 -0.18411927 -0.18175184 ..., -0.11845666 -0.15799969
  -0.33194665]
 [ 0.03934313  0.08632702 -0.04334924 ...,  0.05424636  2.88944227
  -0.06110242]]
Progress: 76.8% ... Training loss: 0.064 ... Validation loss: 0.141[[-0.16706352]
 [-0.95219114]
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 [ 2.58193513]
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[[-0.01802653 -0.30419409  0.26432621 ..., -0.23193574 -0.34486338
   0.25399479]
 [ 0.05843287  0.14593867  0.00420178 ..., -0.22215629  1.56748389
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 [-0.1849708  -0.24243123 -0.37682686 ...,  0.08876791 -0.6054644
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  -0.06193244]]
Progress: 76.8% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16717774]
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 [ 0.03924798  0.08579935 -0.04380234 ...,  0.05408596  2.88953519
  -0.06154492]]
Progress: 76.9% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16533448]
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   0.25347198]
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  -0.3327242 ]
 [ 0.03920148  0.08554233 -0.04406317 ...,  0.05399587  2.88970949
  -0.0617278 ]]
Progress: 76.9% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16810099]
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[[-0.01794291 -0.30382728  0.26503383 ..., -0.23179098 -0.34535948
   0.25506139]
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 [-0.18495517 -0.24232299 -0.37695965 ...,  0.08879304 -0.60430677
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  -0.33188275]
 [ 0.03915975  0.08529308 -0.04435404 ...,  0.05392406  2.88972425
  -0.06181852]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16495026]
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   0.2541641 ]
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  -0.33175062]
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  -0.06206911]]
Progress: 76.9% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16698904]
 [-0.95307607]
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[[-0.01804271 -0.30439786  0.26456911 ..., -0.2319402  -0.34476967
   0.25486604]
 [ 0.05852938  0.14643492  0.0045445  ..., -0.22200134  1.56885995
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 [ 0.03922635  0.08569267 -0.04387727 ...,  0.05405093  2.88962388
  -0.06096304]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16365135]
 [-0.94972571]
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[[-0.01817542 -0.30516381  0.26356287 ..., -0.23217523 -0.34298689
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  -0.33287187]
 [ 0.03910174  0.08496529 -0.04458713 ...,  0.05383002  2.88986004
  -0.0615982 ]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16904644]
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[[-0.01800192 -0.30420947  0.26441983 ..., -0.23187304 -0.34759791
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 [ 0.03908083  0.08481427 -0.04470457 ...,  0.05378795  2.89002554
  -0.06175338]]
Progress: 76.9% ... Training loss: 0.064 ... Validation loss: 0.141[[-0.1669356 ]
 [-0.95111431]
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[[-0.01806061 -0.3045204   0.26428995 ..., -0.23200013 -0.34728283
   0.25354728]
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  -0.33188201]
 [ 0.03910121  0.08492112 -0.04463657 ...,  0.05381807  2.88988575
  -0.06206914]]
Progress: 76.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16600936]
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[[-0.0180281  -0.30436623  0.26457658 ..., -0.23193486 -0.34804746
   0.25423417]
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 [-0.18483095 -0.24161703 -0.37628631 ...,  0.08902875 -0.60527584
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 [ 0.03913135  0.08508664 -0.0444998  ...,  0.05386863  2.88982134
  -0.06166827]]
Progress: 76.9% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16784773]
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[[-0.01789514 -0.30354308  0.26542028 ..., -0.23169182 -0.3502875
   0.25577482]
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 ..., 
 [-0.18475334 -0.2411471  -0.37571521 ...,  0.08918019 -0.60579853
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 [ 0.03915488  0.08523184 -0.04442304 ...,  0.05391325  2.8898208
  -0.06157626]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.15914304]
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[[-0.01824332 -0.30543336  0.26358517 ..., -0.23231199 -0.34613331
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 ..., 
 [-0.18491466 -0.24200233 -0.37664953 ...,  0.08888813 -0.60368568
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  -0.33260317]
 [ 0.03907579  0.08478608 -0.04492826 ...,  0.05376897  2.88988458
  -0.06231012]]
Progress: 76.9% ... Training loss: 0.070 ... Validation loss: 0.150[[-0.16651707]
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[[-0.01796149 -0.3038604   0.26469545 ..., -0.23179434 -0.351861
   0.25550007]
 [ 0.05847958  0.14620788  0.0042841  ..., -0.22209038  1.56948789
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 ..., 
 [-0.18475401 -0.24109954 -0.37575734 ...,  0.08917329 -0.60629818
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 [ 0.03920527  0.08553648 -0.04429837 ...,  0.05400724  2.88957599
  -0.06130887]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16307697]
 [-0.94830513]
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[[-0.01812396 -0.30473467  0.26399328 ..., -0.23209011 -0.35049944
   0.25498446]
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   0.11253607]
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 ..., 
 [-0.18480557 -0.24139159 -0.37597352 ...,  0.08907555 -0.60562007
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  -0.33168022]
 [ 0.03915566  0.08524152 -0.04450151 ...,  0.05391285  2.88945187
  -0.06168646]]
Progress: 76.9% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16906767]
 [-0.954027  ]
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[[-0.01801092 -0.30410843  0.26487293 ..., -0.23189951 -0.35257292
   0.25609064]
 [ 0.05847847  0.14620218  0.00428186 ..., -0.22209221  1.56949079
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 ..., 
 [-0.18472589 -0.24093007 -0.37537434 ...,  0.08920684 -0.60628095
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 [ 0.03923316  0.08571228 -0.04403927 ...,  0.05404524  2.88941118
  -0.06117173]]
Progress: 76.9% ... Training loss: 0.066 ... Validation loss: 0.143[[-0.15972216]
 [-0.94528533]
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  -0.06292042]]
Progress: 76.9% ... Training loss: 0.067 ... Validation loss: 0.145[[-0.16701801]
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 [ 2.58395002]
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 [ 0.03915891  0.08529147 -0.04439203 ...,  0.05389989  2.8895775
  -0.06208811]]
Progress: 77.0% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.15890684]
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  -0.06144839]]
Progress: 77.0% ... Training loss: 0.068 ... Validation loss: 0.150[[-0.166746  ]
 [-0.9530288 ]
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 [ 2.58463185]
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   0.2583222 ]
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 [ 0.0392801   0.08597419 -0.04348251 ...,  0.05411564  2.88942692
  -0.06096899]]
Progress: 77.0% ... Training loss: 0.064 ... Validation loss: 0.144[[-0.16527588]
 [-0.95222783]
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[[-0.01788196 -0.30333046  0.26584311 ..., -0.2316573  -0.34986164
   0.25719873]
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  -0.33231865]
 [ 0.03929271  0.08604972 -0.0433305  ...,  0.05414459  2.88938132
  -0.06069829]]
Progress: 77.0% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16123599]
 [-0.94837934]
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[[-0.01812275 -0.30468385  0.26412837 ..., -0.23206682 -0.34713757
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 [ 0.05844633  0.14600983  0.00408866 ..., -0.22213104  1.5722018
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 [ 0.03927992  0.08598737 -0.04325504 ...,  0.05412254  2.889377
  -0.06075926]]
Progress: 77.0% ... Training loss: 0.064 ... Validation loss: 0.145[[-0.16640727]
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  -0.06151472]]
Progress: 77.0% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.1672191 ]
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[[-0.01781522 -0.30295274  0.26570036 ..., -0.23150181 -0.35190167
   0.25935467]
 [ 0.05858477  0.14678786  0.00462    ..., -0.22187519  1.57089714
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 [ 0.03915143  0.08524013 -0.04444312 ...,  0.05389212  2.88986783
  -0.06188674]]
Progress: 77.0% ... Training loss: 0.064 ... Validation loss: 0.143[[-0.16576986]
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[[-0.01794852 -0.30370045  0.26473605 ..., -0.23172785 -0.34833194
   0.2579004 ]
 [ 0.05851474  0.1463945   0.00407727 ..., -0.22198819  1.57247756
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 [ 0.03922845  0.0856785  -0.0439582  ...,  0.05403168  2.88965734
  -0.06148889]]
Progress: 77.0% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16136853]
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[[-0.0181125  -0.30460502  0.26374624 ..., -0.23202369 -0.34406564
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 [-0.18492057 -0.24196976 -0.37736011 ...,  0.08887477 -0.60341644
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 [ 0.03923739  0.08573841 -0.04381126 ...,  0.05405013  2.88977267
  -0.06167325]]
Progress: 77.0% ... Training loss: 0.066 ... Validation loss: 0.143[[-0.16616905]
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[[-0.01784178 -0.30304163  0.26526408 ..., -0.23153097 -0.34559948
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 [-0.1848731  -0.24170213 -0.3770561  ...,  0.08896524 -0.60457552
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 [ 0.03938051  0.08654161 -0.04284648 ...,  0.05431305  2.88969186
  -0.05992835]]
Progress: 77.0% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16390959]
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[[-0.01794826 -0.30366867  0.26495791 ..., -0.23172422 -0.34551336
   0.25900984]
 [ 0.05844264  0.14599992  0.00374697 ..., -0.22210246  1.57344777
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 ..., 
 [-0.18477136 -0.24112631 -0.37662936 ...,  0.08914624 -0.60600942
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 [ 0.03929588  0.08606343 -0.04325796 ...,  0.05415892  2.88979229
  -0.06069582]]
Progress: 77.0% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16039376]
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[[-0.01819349 -0.30512879  0.26322849 ..., -0.23215683 -0.3431354
   0.25751578]
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 [-0.1849273  -0.24201141 -0.37756785 ...,  0.08887936 -0.60364944
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 [ 0.03926888  0.08586832 -0.04345976 ...,  0.05412476  2.89021376
  -0.06103379]]
Progress: 77.0% ... Training loss: 0.065 ... Validation loss: 0.146[[-0.16620342]
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[[-0.01790242 -0.3035063   0.26460966 ..., -0.23164517 -0.34685226
   0.25999246]
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 [-0.18482378 -0.2414469  -0.37711022 ...,  0.08907133 -0.60572956
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 [ 0.03942384  0.08676272 -0.04284709 ...,  0.05440809  2.89006331
  -0.06011706]]
Progress: 77.0% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16471037]
 [-0.95023601]
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[[-0.01791609 -0.30356395  0.2646058  ..., -0.23166164 -0.34564365
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  -0.06029732]]
Progress: 77.0% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16628015]
 [-0.95248766]
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 [ 2.58739312]
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[[-0.01786302 -0.30327946  0.26496269 ..., -0.23157102 -0.34724486
   0.2605056 ]
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  -0.33446151]
 [ 0.03935521  0.08637449 -0.04310122 ...,  0.0542934   2.89063919
  -0.06030699]]
Progress: 77.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16786135]
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 [ 2.58707899]
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 [-0.18477759 -0.24118571 -0.37700044 ...,  0.08916786 -0.60558684
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  -0.33382783]
 [ 0.03936467  0.08639664 -0.04322334 ...,  0.0542975   2.8905727
  -0.06021926]]
Progress: 77.1% ... Training loss: 0.065 ... Validation loss: 0.141[[-0.15914638]
 [-0.94704542]
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 [ 2.59130388]
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[[-0.01811842 -0.30462356  0.2632064  ..., -0.23201487 -0.34212932
   0.25844243]
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  -0.33455167]
 [ 0.03933773  0.08623558 -0.04334635 ...,  0.05424703  2.89058683
  -0.0604417 ]]
Progress: 77.1% ... Training loss: 0.067 ... Validation loss: 0.149[[-0.16947811]
 [-0.95597996]
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 [ 2.58634405]
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  -0.33244764]
 [ 0.03954806  0.08744834 -0.04207733 ...,  0.05463543  2.89035265
  -0.05889019]]
Progress: 77.1% ... Training loss: 0.068 ... Validation loss: 0.143[[-0.16181099]
 [-0.94918348]
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   0.2623388 ]
 [ 0.05855964  0.14668393  0.00465091 ..., -0.22190653  1.57251245
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  -0.33335773]
 [ 0.03948866  0.08710395 -0.04237017 ...,  0.05452086  2.89040105
  -0.05914481]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16184098]
 [-0.94931116]
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 [ 2.58971947]
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[[-0.01775818 -0.3024313   0.26569079 ..., -0.23132808 -0.34334005
   0.26297215]
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 [ 0.0395062   0.08719088 -0.04229334 ...,  0.05456035  2.89043194
  -0.05944467]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16296886]
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[[-0.0178388  -0.30302111  0.26482019 ..., -0.23148815 -0.34400864
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 [ 0.05857063  0.14673646  0.00469507 ..., -0.22188517  1.57265536
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 [ 0.03968792  0.08822312 -0.04113725 ...,  0.0549006   2.8901206
  -0.0575477 ]]
Progress: 77.1% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16112184]
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[[-0.01788336 -0.30332048  0.26458456 ..., -0.23160471 -0.34408137
   0.26148084]
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 ..., 
 [-0.18487365 -0.24172103 -0.37746297 ...,  0.08901    -0.60458413
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  -0.33475651]
 [ 0.03959157  0.0876971  -0.04160352 ...,  0.05473094  2.89028697
  -0.05854893]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16447719]
 [-0.95134983]
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[[-0.01775007 -0.30252853  0.26563066 ..., -0.23135748 -0.34632685
   0.26342743]
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 [-0.18482449 -0.24143102 -0.37736024 ...,  0.0891001  -0.60537835
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  -0.33420669]
 [ 0.0396779   0.0881962  -0.04094731 ...,  0.05488416  2.89012188
  -0.05748339]]
Progress: 77.1% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16191934]
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[[-0.01770806 -0.30228235  0.26589983 ..., -0.231288   -0.34677293
   0.26392277]
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 [-0.18483807 -0.24149762 -0.37755092 ...,  0.08907624 -0.60516726
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 [ 0.03971945  0.08839653 -0.04067519 ...,  0.05494782  2.89004847
  -0.05710145]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16473177]
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[[-0.01771652 -0.30223293  0.26608191 ..., -0.23129258 -0.34568709
   0.26469391]
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 ..., 
 [-0.18482974 -0.24141225 -0.37753141 ...,  0.08909037 -0.60519827
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 [ 0.03980772  0.08885641 -0.04004115 ...,  0.05510734  2.89001254
  -0.05598243]]
Progress: 77.1% ... Training loss: 0.064 ... Validation loss: 0.141[[-0.16465914]
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[[-0.01765625 -0.3019213   0.2666665  ..., -0.23119388 -0.34622159
   0.26462411]
 [ 0.05866036  0.14724812  0.00518273 ..., -0.22172482  1.5722082
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 ..., 
 [-0.18488147 -0.24170565 -0.3778173  ...,  0.0889929  -0.60378285
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 [ 0.0397382   0.08844329 -0.04026537 ...,  0.05498517  2.89021917
  -0.05654053]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16173784]
 [-0.95075335]
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[[-0.01770665 -0.30215202  0.2662214  ..., -0.23127659 -0.34386265
   0.26451018]
 [ 0.05868282  0.14737506  0.00532906 ..., -0.22168725  1.5720956
   0.11444364]
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   0.96559856]
 ..., 
 [-0.18489772 -0.24181248 -0.37767754 ...,  0.08895813 -0.60282989
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  -0.33533226]
 [ 0.03976266  0.08856641 -0.04017716 ...,  0.05503307  2.89019142
  -0.05626118]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16169079]
 [-0.95000669]
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[[-0.01779758 -0.30268062  0.26586317 ..., -0.23144658 -0.34225489
   0.26368503]
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 [-0.18488394 -0.24175443 -0.37762757 ...,  0.0889817  -0.60301897
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 [ 0.03981556  0.08888785 -0.03991074 ...,  0.05512439  2.89008305
  -0.05595487]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16149642]
 [-0.94941417]
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[[-0.01777598 -0.30257696  0.26597478 ..., -0.23141655 -0.34190905
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 [ 0.03979962  0.08878004 -0.03990851 ...,  0.0550977   2.89025382
  -0.0563817 ]]
Progress: 77.1% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16620245]
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  -0.0562248 ]]
Progress: 77.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16484441]
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   0.26476486]
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  -0.33667212]
 [ 0.03975917  0.08855771 -0.04006872 ...,  0.05501819  2.8901652
  -0.05650071]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16410614]
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 [ 0.03980136  0.08879932 -0.03992186 ...,  0.05509446  2.89011878
  -0.05612419]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16483684]
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[[-0.01739356 -0.30034106  0.26789213 ..., -0.23073527 -0.34281148
   0.26738309]
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 [ 0.039716    0.08831957 -0.04040519 ...,  0.054938    2.89015293
  -0.0564691 ]]
Progress: 77.2% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16531498]
 [-0.95169829]
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[[-0.01734015 -0.30000622  0.26803431 ..., -0.23062227 -0.3424344
   0.26723925]
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 [ 0.03950817  0.08709942 -0.04159475 ...,  0.05455871  2.89049508
  -0.05811526]]
Progress: 77.2% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16058895]
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   0.26593706]
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 [ 0.03939923  0.08649011 -0.04203975 ...,  0.05436754  2.89066058
  -0.05909092]]
Progress: 77.2% ... Training loss: 0.065 ... Validation loss: 0.141[[-0.16995418]
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[[-0.01694671 -0.29772599  0.27022969 ..., -0.22990496 -0.3494875
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 [ 0.03938219  0.0863909  -0.04215663 ...,  0.0543356   2.89067225
  -0.05933491]]
Progress: 77.2% ... Training loss: 0.069 ... Validation loss: 0.145[[-0.16007717]
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[[-0.01727484 -0.29955024  0.26845093 ..., -0.2304798  -0.34717388
   0.26760349]
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 [ 0.03928462  0.0858304  -0.04291501 ...,  0.0541565   2.89081356
  -0.06018792]]
Progress: 77.2% ... Training loss: 0.065 ... Validation loss: 0.144[[-0.16695496]
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[[-0.01728142 -0.29960812  0.2680385  ..., -0.23046514 -0.34735387
   0.26746807]
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 [ 0.03934915  0.08618119 -0.04245704 ...,  0.05427956  2.89077733
  -0.05987394]]
Progress: 77.2% ... Training loss: 0.065 ... Validation loss: 0.142[[-0.16343203]
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[[-0.01753851 -0.30104508  0.26617251 ..., -0.23093064 -0.34371784
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 [ 0.03923763  0.0855487  -0.04310444 ...,  0.05408002  2.89107077
  -0.06104275]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16362067]
 [-0.95074951]
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[[-0.01742919 -0.3003852   0.26676296 ..., -0.23072575 -0.34496238
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 ..., 
 [-0.18500084 -0.24238572 -0.37873262 ...,  0.0887833  -0.59988951
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 [ 0.0392533   0.08563671 -0.04297972 ...,  0.05410807  2.89102878
  -0.06071145]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16500733]
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[[-0.01736911 -0.2999914   0.26733832 ..., -0.23061931 -0.34587696
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 [-0.18499316 -0.24234775 -0.3786126  ...,  0.08879174 -0.59949564
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  -0.06086006]]
Progress: 77.2% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16301175]
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[[-0.01733149 -0.29978383  0.26759626 ..., -0.23056127 -0.34559378
   0.26754257]
 [ 0.05840213  0.14581884  0.00334    ..., -0.22216621  1.57722245
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 [-0.1850282  -0.24255795 -0.37850037 ...,  0.08872822 -0.59897324
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 [ 0.03914018  0.084978   -0.04355617 ...,  0.0539106   2.89112873
  -0.061415  ]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16518947]
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[[-0.01729539 -0.29959208  0.26763663 ..., -0.23051771 -0.3447311
   0.26762702]
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  -0.06128175]]
Progress: 77.2% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16635999]
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 [-1.08075151]
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[[-0.01741086 -0.30018901  0.26712393 ..., -0.23070672 -0.34209265
   0.2668656 ]
 [ 0.05842208  0.14590686  0.00362058 ..., -0.22215852  1.5776866
   0.11215498]
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  -0.33679806]
 [ 0.03927583  0.08574059 -0.04265672 ...,  0.05415769  2.89068131
  -0.05988724]]
Progress: 77.2% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.16472957]
 [-0.95115629]
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 [ 2.59266789]
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[[-0.0172755  -0.29940275  0.26808108 ..., -0.2304555  -0.34212481
   0.26757008]
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  -0.3377381 ]
 [ 0.03934427  0.08612605 -0.04238136 ...,  0.05427596  2.89055869
  -0.05950701]]
Progress: 77.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16676591]
 [-0.95206796]
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[[-0.01715256 -0.29875764  0.268492   ..., -0.23023864 -0.34476632
   0.26811664]
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 [-0.18490694 -0.24189866 -0.3778956  ...,  0.0889607  -0.60016666
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  -0.33792083]
 [ 0.03944416  0.08670461 -0.04192015 ...,  0.05445741  2.8903555
  -0.05845959]]
Progress: 77.3% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16369931]
 [-0.94943204]
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 [ 2.59194485]
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[[-0.0173425  -0.29976975  0.26736347 ..., -0.23058308 -0.3406494
   0.26679601]
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  -0.33805168]
 [ 0.03933154  0.08608707 -0.04255134 ...,  0.05425112  2.89057473
  -0.05940486]]
Progress: 77.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16047409]
 [-0.94562044]
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 [ 2.59438184]
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[[-0.01752948 -0.3008847   0.26663475 ..., -0.23092354 -0.33912515
   0.26524932]
 [ 0.05832915  0.14537594  0.00323712 ..., -0.22232413  1.57747721
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 [-0.18495181 -0.24211553 -0.37807242 ...,  0.08886641 -0.59946284
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  -0.33857686]
 [ 0.03936267  0.08626652 -0.0423416  ...,  0.05430027  2.89052398
  -0.05904012]]
Progress: 77.3% ... Training loss: 0.065 ... Validation loss: 0.142[[-0.16763514]
 [-0.95007177]
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 [ 2.5922661 ]
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[[-0.01735105 -0.29990364  0.26795154 ..., -0.23059852 -0.3404478
   0.2662203 ]
 [ 0.05834177  0.14548099  0.00349172 ..., -0.22230386  1.57721691
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 [-0.18492881 -0.24198207 -0.37787748 ...,  0.08890529 -0.59990925
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  -0.33787399]
 [ 0.0393531   0.08621799 -0.04275996 ...,  0.05428103  2.89054485
  -0.0595965 ]]
Progress: 77.3% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16437661]
 [-0.94798218]
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 [ 2.59326137]
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[[-0.0174675  -0.30051937  0.26713638 ..., -0.23079937 -0.33809053
   0.26567831]
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  -0.33736532]
 [ 0.0393556   0.08622481 -0.04275095 ...,  0.05427876  2.89039141
  -0.05945578]]
Progress: 77.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16636425]
 [-0.94992449]
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[[-0.01740103 -0.30016315  0.26706102 ..., -0.23069263 -0.33764608
   0.26547248]
 [ 0.05833504  0.14545018  0.0033939  ..., -0.22231609  1.57730855
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 [-0.18496004 -0.24216617 -0.37813975 ...,  0.08884752 -0.60006206
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  -0.33724497]
 [ 0.03940452  0.08651808 -0.04238261 ...,  0.05436846  2.89028871
  -0.05906952]]
Progress: 77.3% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16544983]
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[[-0.01743949 -0.3004054   0.2665487  ..., -0.23075092 -0.338971
   0.26519929]
 [ 0.05831991  0.14537084  0.00330023 ..., -0.22234164  1.57737934
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 [-0.18495761 -0.24215426 -0.37822778 ...,  0.08885233 -0.59979628
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  -0.33774515]
 [ 0.03928517  0.08583307 -0.04305046 ...,  0.05414353  2.89058959
  -0.06029507]]
Progress: 77.3% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.1612381 ]
 [-0.9454529 ]
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[[-0.01777902 -0.30230203  0.26444276 ..., -0.2313642  -0.33410822
   0.26230834]
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 [-0.18500849 -0.2424064  -0.3782521  ...,  0.08875217 -0.59821925
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  -0.33804399]
 [ 0.03921291  0.08543896 -0.0432909  ...,  0.05401296  2.89073435
  -0.0606814 ]]
Progress: 77.3% ... Training loss: 0.065 ... Validation loss: 0.140[[-0.1677986 ]
 [-0.95071763]
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[[-0.01764146 -0.3014639   0.26543827 ..., -0.23112266 -0.33426208
   0.26314778]
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 [-0.18499682 -0.24234064 -0.37815766 ...,  0.08877561 -0.59800311
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  -0.33789483]
 [ 0.03920037  0.08535855 -0.04333492 ...,  0.05398778  2.89094072
  -0.06113533]]
Progress: 77.3% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.16644878]
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[[-0.01764369 -0.30152199  0.26513836 ..., -0.23112993 -0.33550633
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 ..., 
 [-0.18499029 -0.24228558 -0.37800568 ...,  0.08879255 -0.59820117
  -0.318736  ]
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  -0.337518  ]
 [ 0.03934797  0.08618441 -0.04244946 ...,  0.05424225  2.89043244
  -0.05997055]]
Progress: 77.3% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16761964]
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[[-0.01762092 -0.30134514  0.26534761 ..., -0.23106349 -0.33374036
   0.26395734]
 [ 0.05837621  0.14561987  0.00356782 ..., -0.22225645  1.57802606
   0.11267995]
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 ..., 
 [-0.18502169 -0.24247248 -0.37802606 ...,  0.08873969 -0.598023
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  -0.33805818]
 [ 0.03949479  0.08700641 -0.04163541 ...,  0.05450414  2.89021531
  -0.05890739]]
Progress: 77.3% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16302996]
 [-0.94765904]
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[[-0.01770396 -0.30180826  0.26515665 ..., -0.2312233  -0.33409948
   0.26328245]
 [ 0.05838949  0.1456931   0.00361612 ..., -0.2222351   1.57792924
   0.11276045]
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 [-0.18503979 -0.24256622 -0.37809858 ...,  0.08870706 -0.59775723
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 [-0.27611973 -0.18673664 -0.18436512 ..., -0.11930397 -0.1501421
  -0.33765773]
 [ 0.03939489  0.08644625 -0.0419454  ...,  0.05432896  2.8902899
  -0.05984771]]
Progress: 77.3% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16653746]
 [-0.95080222]
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[[-0.01751329 -0.3007191   0.26637237 ..., -0.2308779  -0.33741444
   0.26480006]
 [ 0.05839184  0.14570639  0.00362403 ..., -0.22223067  1.57792773
   0.11277128]
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  -0.3365358 ]
 [ 0.03935365  0.08621287 -0.04208094 ...,  0.05425286  2.89030494
  -0.0604133 ]]
Progress: 77.3% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.1590213 ]
 [-0.94475952]
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 [ 2.5960892 ]
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[[-0.01780171 -0.30233818  0.26501678 ..., -0.23139803 -0.33457869
   0.26252297]
 [ 0.05838644  0.14566642  0.00361167 ..., -0.22224116  1.57805495
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  -0.33721019]
 [ 0.03924054  0.08556922 -0.04269154 ...,  0.05404204  2.89059315
  -0.0614884 ]]
Progress: 77.3% ... Training loss: 0.067 ... Validation loss: 0.143[[-0.1672933 ]
 [-0.95198072]
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[[-0.01758896 -0.301161    0.2659218  ..., -0.23100848 -0.33693187
   0.26428884]
 [ 0.05840605  0.14576691  0.00366902 ..., -0.22220534  1.57799178
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  -0.33586437]
 [ 0.03932057  0.0860313  -0.04238846 ...,  0.05418871  2.89054691
  -0.06087593]]
Progress: 77.3% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.1638839 ]
 [-0.94928456]
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   0.26244648]
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  -0.33669153]
 [ 0.03919762  0.08535801 -0.04335397 ...,  0.05397287  2.89115398
  -0.06203354]]
Progress: 77.4% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16816334]
 [-0.95351126]
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 [ 2.59251939]
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  -0.33605911]
 [ 0.03930064  0.08594621 -0.04272015 ...,  0.05417083  2.89102986
  -0.06105451]]
Progress: 77.4% ... Training loss: 0.066 ... Validation loss: 0.138[[-0.16818184]
 [-0.95388342]
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[[-0.01772324 -0.30191725  0.26480996 ..., -0.23120417 -0.33717482
   0.26276226]
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  -0.33524499]
 [ 0.03929386  0.08587862 -0.04282561 ...,  0.05415787  2.89107151
  -0.06150321]]
Progress: 77.4% ... Training loss: 0.066 ... Validation loss: 0.139[[-0.15941093]
 [-0.94611509]
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[[-0.01818985 -0.30451095  0.26219945 ..., -0.23203942 -0.33114393
   0.25903336]
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  -0.33592424]
 [ 0.03906785  0.08461595 -0.04392369 ...,  0.05373885  2.89151126
  -0.06315818]]
Progress: 77.4% ... Training loss: 0.066 ... Validation loss: 0.143[[-0.16705223]
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[[-0.01794511 -0.30309843  0.26342393 ..., -0.23158663 -0.33424011
   0.261119  ]
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  -0.3359866 ]
 [ 0.03909858  0.08479943 -0.0438525  ...,  0.05379855  2.89154779
  -0.06318234]]
Progress: 77.4% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16440849]
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[[-0.01805991 -0.30367226  0.26299207 ..., -0.23176734 -0.33326646
   0.2602567 ]
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  -0.33653679]
 [ 0.03904104  0.08446469 -0.04428408 ...,  0.05368421  2.89155836
  -0.06383723]]
Progress: 77.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.1630928 ]
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[[-0.0181332  -0.30401829  0.26248844 ..., -0.23188494 -0.33209669
   0.26002482]
 [ 0.05849885  0.14634546  0.00376092 ..., -0.22203293  1.57878216
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 [-0.18460281 -0.24008941 -0.3756047  ...,  0.08952655 -0.60271847
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 [ 0.03909487  0.08476169 -0.04377125 ...,  0.05379089  2.89154928
  -0.06348168]]
Progress: 77.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16644908]
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[[-0.01803566 -0.30345028  0.26306275 ..., -0.23169828 -0.33335046
   0.26079252]
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 [-0.18456356 -0.23987446 -0.37541564 ...,  0.08959808 -0.6026028
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 [ 0.03904819  0.08446784 -0.04394318 ...,  0.05370467  2.89164164
  -0.0636965 ]]
Progress: 77.4% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.1592563 ]
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[[-0.01842705 -0.30557721  0.26116038 ..., -0.23240285 -0.32991526
   0.25688673]
 [ 0.05846393  0.14619446  0.00359301 ..., -0.22209275  1.57870405
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 ..., 
 [-0.18466505 -0.24042012 -0.37580139 ...,  0.08941981 -0.600675
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 [ 0.03898776  0.08411231 -0.04426739 ...,  0.05359704  2.89188668
  -0.06470905]]
Progress: 77.4% ... Training loss: 0.068 ... Validation loss: 0.144[[-0.16694312]
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[[-0.01808507 -0.30366579  0.26332476 ..., -0.23180089 -0.33439588
   0.2591926 ]
 [ 0.05848687  0.14629865  0.00366447 ..., -0.22205782  1.57871169
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 ..., 
 [-0.18459815 -0.24005873 -0.37526906 ...,  0.08954279 -0.60209813
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 [ 0.03900195  0.08419842 -0.04428227 ...,  0.05362201  2.89204648
  -0.06466975]]
Progress: 77.4% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16262743]
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[[-0.01822454 -0.30436403  0.26314056 ..., -0.23203183 -0.33383363
   0.25884278]
 [ 0.058484    0.14628376  0.00375493 ..., -0.22206054  1.57853749
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 [-0.18460992 -0.2401155  -0.37543003 ...,  0.08950456 -0.60207882
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  -0.33687248]
 [ 0.03891213  0.08370428 -0.0445616  ...,  0.05345821  2.89222661
  -0.06536737]]
Progress: 77.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16747201]
 [-0.95354971]
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[[-0.01793957 -0.30273499  0.26495131 ..., -0.23149604 -0.33582797
   0.26191786]
 [ 0.05854337  0.14664815  0.0040991  ..., -0.22194586  1.57771399
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 [-0.18460571 -0.24009313 -0.37548755 ...,  0.08951453 -0.60234011
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 [ 0.03903356  0.08440255 -0.04378865 ...,  0.05367603  2.8921632
  -0.06422816]]
Progress: 77.4% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.16151654]
 [-0.94749152]
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[[-0.01811079 -0.30362489  0.26402048 ..., -0.23180195 -0.33452306
   0.26097594]
 [ 0.05854891  0.1466878   0.0039898  ..., -0.22193685  1.57796423
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 [ 0.03891093  0.08375433 -0.04464449 ...,  0.05345505  2.89242394
  -0.06567105]]
Progress: 77.4% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.16584537]
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[[-0.01794691 -0.30270605  0.26476063 ..., -0.2314962  -0.33618958
   0.26339616]
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 [ 0.03899884  0.08428301 -0.04414746 ...,  0.05362722  2.89232989
  -0.06494811]]
Progress: 77.4% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.1634254 ]
 [-0.95060882]
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[[-0.01820116 -0.30410537  0.2634313  ..., -0.23194797 -0.33242414
   0.26142504]
 [ 0.05863241  0.14710501  0.00456289 ..., -0.2217812   1.57751859
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  -0.33760502]
 [ 0.03884322  0.08338581 -0.04485406 ...,  0.05333801  2.89259835
  -0.06592774]]
Progress: 77.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16444999]
 [-0.95158317]
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[[-0.01833768 -0.30486922  0.26254151 ..., -0.23217409 -0.33283779
   0.26059274]
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  -0.33721447]
 [ 0.03879037  0.08307394 -0.04545759 ...,  0.05324958  2.89270495
  -0.06659554]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16227369]
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   0.25947484]
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  -0.33642222]
 [ 0.03863538  0.08218757 -0.04630376 ...,  0.05295463  2.8929321
  -0.06797341]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.1618821 ]
 [-0.94911909]
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[[-0.01847068 -0.30557887  0.26188124 ..., -0.23245297 -0.33310287
   0.25902831]
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  -0.33591475]
 [ 0.03860084  0.082029   -0.04654546 ...,  0.05289644  2.89303943
  -0.06848049]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16274748]
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[[-0.01836622 -0.30499875  0.26263293 ..., -0.23227834 -0.33402244
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  -0.33555915]
 [ 0.03861963  0.08213216 -0.04630788 ...,  0.05292786  2.89304283
  -0.06830685]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.16211986]
 [-0.94788823]
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[[-0.01842807 -0.30536517  0.26216694 ..., -0.23238827 -0.33317503
   0.25957683]
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 [-0.18478103 -0.24103589 -0.37718957 ...,  0.0892284  -0.60045182
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  -0.33595106]
 [ 0.03863421  0.0822482  -0.04638338 ...,  0.0529637   2.89305121
  -0.0681887 ]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.16513584]
 [-0.95012384]
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[[-0.01832286 -0.30481607  0.26239752 ..., -0.23219099 -0.33332442
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 [-0.18475355 -0.24088584 -0.37699778 ...,  0.0892789  -0.6015025
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  -0.33616543]
 [ 0.03873009  0.08281146 -0.04597156 ...,  0.05313701  2.89292301
  -0.06736876]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.16309975]
 [-0.94935167]
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[[-0.01834104 -0.30497613  0.26227694 ..., -0.23223691 -0.33325039
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 ..., 
 [-0.18477318 -0.24100696 -0.37712829 ...,  0.08924304 -0.60127265
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  -0.33635598]
 [ 0.03863673  0.08227339 -0.04630055 ...,  0.05296896  2.89297254
  -0.06755865]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16301134]
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[[-0.01832725 -0.30494519  0.26237756 ..., -0.23221621 -0.33431317
   0.26023311]
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 ..., 
 [-0.18476582 -0.24099147 -0.37722138 ...,  0.08925522 -0.60136873
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  -0.33669203]
 [ 0.0386393   0.08228979 -0.04622788 ...,  0.05297311  2.89295119
  -0.06765829]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16558248]
 [-0.95088457]
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[[-0.01814895 -0.30389788  0.26362169 ..., -0.23189921 -0.33550211
   0.26142365]
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 [-0.18471618 -0.2407075  -0.37718684 ...,  0.08936274 -0.60163505
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 [-0.27592397 -0.18543828 -0.18274385 ..., -0.1189539  -0.15304128
  -0.33611341]
 [ 0.03859273  0.08202802 -0.04653582 ...,  0.05289209  2.89323638
  -0.06859281]]
Progress: 77.5% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16292352]
 [-0.94851063]
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[[-0.01801938 -0.30313974  0.26371065 ..., -0.23165638 -0.33447049
   0.26273195]
 [ 0.05879033  0.14789611  0.00549849 ..., -0.22150644  1.57836343
   0.11620236]
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 ..., 
 [-0.18483335 -0.24137197 -0.37777376 ...,  0.08915851 -0.60031571
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  -0.33572758]
 [ 0.03862673  0.08221081 -0.04669159 ...,  0.05295218  2.89314012
  -0.06845174]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16099691]
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[[-0.018138   -0.30386795  0.26317212 ..., -0.23186631 -0.33172499
   0.26169512]
 [ 0.05879033  0.14789611  0.00549849 ..., -0.22150644  1.57836343
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 [-0.18489896 -0.24174469 -0.37821257 ...,  0.08903949 -0.59933078
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  -0.33637502]
 [ 0.03862874  0.08218919 -0.04668264 ...,  0.05295939  2.89330631
  -0.06831931]]
Progress: 77.5% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16921786]
 [-0.95438638]
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[[-0.01789479 -0.30252974  0.26431658 ..., -0.23144719 -0.33704035
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 [ 0.05886239  0.14830703  0.00574563 ..., -0.22137617  1.57778936
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 [-0.18476952 -0.24101809 -0.37768379 ...,  0.0892744  -0.60197196
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  -0.06859237]]
Progress: 77.5% ... Training loss: 0.069 ... Validation loss: 0.141[[-0.16370911]
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[[-0.01816971 -0.30397527  0.26291862 ..., -0.2319141  -0.33371785
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  -0.06911721]]
Progress: 77.5% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.1589708 ]
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   0.25906877]
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  -0.06984229]]
Progress: 77.5% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.1672472 ]
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 [ 0.03871235  0.08276018 -0.04632928 ...,  0.05310755  2.89335277
  -0.06807762]]
Progress: 77.5% ... Training loss: 0.066 ... Validation loss: 0.138[[-0.16166439]
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  -0.06860234]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16355133]
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[[-0.01839016 -0.30504698  0.26167296 ..., -0.23224949 -0.33276022
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  -0.06817336]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16533727]
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  -0.06886659]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.16477972]
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 [ 0.03873977  0.08292521 -0.04606203 ...,  0.0531592   2.89323961
  -0.06815657]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.164822  ]
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[[-0.01814183 -0.30366212  0.26302192 ..., -0.23181787 -0.33332543
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 [ 0.03869634  0.08270332 -0.04641502 ...,  0.05308903  2.89333734
  -0.06832811]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.15816881]
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 [ 0.03873805  0.08294844 -0.04638764 ...,  0.05316808  2.89325293
  -0.06799279]]
Progress: 77.6% ... Training loss: 0.066 ... Validation loss: 0.143[[-0.1638601 ]
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[[-0.01836161 -0.30494016  0.2617558  ..., -0.23221233 -0.32720859
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 [-0.18491305 -0.24186154 -0.3787444  ...,  0.08902688 -0.5981218
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 [ 0.03883661  0.08351464 -0.04586355 ...,  0.05334719  2.89308204
  -0.06723655]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16200976]
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[[-0.0183402  -0.30482567  0.26212011 ..., -0.23217693 -0.32745157
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 ..., 
 [-0.18499431 -0.2423049  -0.37904513 ...,  0.08888182 -0.59676038
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 [ 0.03882402  0.08343586 -0.04612952 ...,  0.05331887  2.89306294
  -0.06737238]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.1593297 ]
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[[-0.01841156 -0.30527174  0.26165009 ..., -0.23229602 -0.32706673
   0.25815123]
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 ..., 
 [-0.1850894  -0.24283286 -0.37945617 ...,  0.08871083 -0.59603371
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 [ 0.03883262  0.08349291 -0.04584621 ...,  0.05333408  2.89308573
  -0.06699849]]
Progress: 77.6% ... Training loss: 0.065 ... Validation loss: 0.142[[-0.1611877 ]
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[[-0.01828906 -0.30462546  0.26246283 ..., -0.2320856  -0.32831841
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 [-0.18506998 -0.24274646 -0.37919987 ...,  0.08874494 -0.59644366
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 [ 0.03889272  0.08383084 -0.04552113 ...,  0.05344311  2.89300843
  -0.06677312]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16197867]
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[[-0.01818121 -0.30404689  0.26314094 ..., -0.23188022 -0.33067571
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 [-0.18515739 -0.24325593 -0.37978004 ...,  0.08858233 -0.59524221
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 [ 0.03886336  0.08365471 -0.04582013 ...,  0.05338533  2.89302298
  -0.06708513]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.1643099 ]
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[[-0.01819014 -0.30410321  0.26338029 ..., -0.23186362 -0.33016717
   0.26063772]
 [ 0.05919761  0.15020289  0.00717133 ..., -0.22079042  1.57571408
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  -0.339298  ]
 [ 0.03901248  0.084422   -0.04478089 ...,  0.05364888  2.89291381
  -0.066135  ]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16387105]
 [-0.95005828]
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 [ 2.59658664]
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   0.26124553]
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 [ 0.03901223  0.08439808 -0.04482654 ...,  0.05364549  2.89278331
  -0.06634407]]
Progress: 77.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16050082]
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[[-0.01839962 -0.30540259  0.26252091 ..., -0.23224566 -0.3284466
   0.25894184]
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  -0.33974855]
 [ 0.03888784  0.08367515 -0.04575249 ...,  0.05341615  2.89304078
  -0.06761634]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.16129883]
 [-0.94752805]
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[[-0.01838854 -0.30541861  0.26282404 ..., -0.23220578 -0.32903502
   0.25962651]
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  -0.33955735]
 [ 0.03893718  0.08393372 -0.04558974 ...,  0.05350145  2.89302175
  -0.06752581]]
Progress: 77.6% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16154403]
 [-0.94739374]
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[[-0.01845011 -0.30583932  0.26249267 ..., -0.23232901 -0.32814585
   0.25858317]
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  -0.33944753]
 [ 0.03897091  0.08411939 -0.04544965 ...,  0.05356645  2.89298955
  -0.06764163]]
Progress: 77.7% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16494387]
 [-0.95031563]
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[[-0.01840877 -0.3056248   0.26276971 ..., -0.23225888 -0.32811065
   0.25921177]
 [ 0.05907437  0.14945086  0.00670322 ..., -0.22100864  1.57651939
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  -0.3398978 ]
 [ 0.0391279   0.08505069 -0.0445666  ...,  0.05385416  2.89293476
  -0.06614658]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16876195]
 [-0.95427081]
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[[-0.01837041 -0.30540094  0.26312735 ..., -0.23219174 -0.32938571
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  -0.339482  ]
 [ 0.03918063  0.0853442  -0.04424647 ...,  0.05395067  2.8929187
  -0.0658668 ]]
Progress: 77.7% ... Training loss: 0.066 ... Validation loss: 0.139[[-0.15775581]
 [-0.94359591]
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[[-0.01853806 -0.30627736  0.26237205 ..., -0.23247052 -0.32691612
   0.25833855]
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 [-0.18490846 -0.24190779 -0.37889164 ...,  0.08906344 -0.59930277
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  -0.34074007]
 [ 0.03913412  0.085074   -0.04417814 ...,  0.05387562  2.89293019
  -0.06615496]]
Progress: 77.7% ... Training loss: 0.069 ... Validation loss: 0.152[[-0.16679295]
 [-0.95037931]
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[[-0.01811703 -0.30392188  0.26494488 ..., -0.23169999 -0.33132681
   0.26154741]
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 [ 0.03925039  0.08573751 -0.04330261 ...,  0.05409526  2.89284447
  -0.06532867]]
Progress: 77.7% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16401129]
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[[-0.01801487 -0.30327732  0.26545552 ..., -0.23149676 -0.33156819
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 [-0.18474618 -0.24100097 -0.37786595 ...,  0.08936259 -0.60229513
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 [ 0.03905089  0.08461338 -0.04473046 ...,  0.05373575  2.89322555
  -0.06702345]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16336763]
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[[-0.01801458 -0.30327132  0.26540442 ..., -0.23149476 -0.33184607
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 [-0.18475698 -0.24106227 -0.37785593 ...,  0.08933606 -0.602219
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 [ 0.0389975   0.08431551 -0.04524668 ...,  0.05363541  2.89321955
  -0.06728936]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16951505]
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[[-0.01781008 -0.30209905  0.26650112 ..., -0.2311195  -0.33328504
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 [-0.18465123 -0.24047752 -0.3776655  ...,  0.08953084 -0.60349179
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  -0.34198959]
 [ 0.03915345  0.08523942 -0.0442069  ...,  0.05392613  2.89325388
  -0.06664856]]
Progress: 77.7% ... Training loss: 0.066 ... Validation loss: 0.139[[-0.16263847]
 [-0.94542819]
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[[-0.01803638 -0.30330129  0.26549106 ..., -0.23149397 -0.33070929
   0.26271674]
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 [-0.18471851 -0.24083552 -0.37791979 ...,  0.08941901 -0.60276545
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  -0.34228804]
 [ 0.03911405  0.08499854 -0.04430946 ...,  0.05385731  2.89337359
  -0.06725394]]
Progress: 77.7% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16675342]
 [-0.94950834]
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[[-0.01788127 -0.30237038  0.26629247 ..., -0.23119473 -0.3329069
   0.26384154]
 [ 0.05897922  0.14891881  0.0060497  ..., -0.22116796  1.57765425
   0.1179384 ]
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 [-0.18461571 -0.24022614 -0.37734585 ...,  0.08959838 -0.60358159
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  -0.34235202]
 [ 0.03918845  0.08538374 -0.04379793 ...,  0.0539899   2.8934049
  -0.06635959]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.159965  ]
 [-0.94365974]
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[[-0.01805604 -0.30342375  0.26486673 ..., -0.23151663 -0.33393901
   0.26198365]
 [ 0.0589395   0.14869595  0.0057738  ..., -0.22123983  1.5781912
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 [-0.18449314 -0.23954379 -0.37667551 ...,  0.08982254 -0.60529812
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 [ 0.03893635  0.08394795 -0.04528918 ...,  0.05352584  2.89391718
  -0.06904785]]
Progress: 77.7% ... Training loss: 0.064 ... Validation loss: 0.142[[-0.16607127]
 [-0.94880602]
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[[-0.01774753 -0.30173403  0.26683273 ..., -0.23095696 -0.33994057
   0.26411014]
 [ 0.05894843  0.14875524  0.00580654 ..., -0.22122247  1.57823485
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 [-0.18447838 -0.23948063 -0.3765688  ...,  0.08985234 -0.60566332
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  -0.34208993]
 [ 0.03888418  0.0836493  -0.04542181 ...,  0.05342267  2.89383274
  -0.06939796]]
Progress: 77.7% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16247101]
 [-0.94556516]
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 [-0.04729356]
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[[-0.0179265  -0.30273402  0.26586377 ..., -0.2312792  -0.33891839
   0.2625553 ]
 [ 0.05890438  0.14849609  0.00537886 ..., -0.2213027   1.57839753
   0.11713477]
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  -0.34188774]
 [ 0.03887619  0.08360382 -0.04550022 ...,  0.05341269  2.89393373
  -0.06966864]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16526446]
 [-0.94766257]
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[[-0.01787936 -0.30246617  0.26606665 ..., -0.23121761 -0.34048419
   0.26253435]
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   0.11714875]
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  -0.34173613]
 [ 0.03891102  0.0838138  -0.04535213 ...,  0.05347469  2.89384631
  -0.0695902 ]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16280216]
 [-0.94557215]
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 [ 2.59975563]
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[[-0.01802865 -0.30330477  0.26519647 ..., -0.23147504 -0.33902628
   0.26164175]
 [ 0.0588932   0.14842224  0.00527997 ..., -0.22133487  1.57811746
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 [-0.18462994 -0.24032193 -0.37779368 ...,  0.08957485 -0.60336779
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  -0.34238035]
 [ 0.03887047  0.08358126 -0.04544604 ...,  0.05340032  2.89402865
  -0.06981785]]
Progress: 77.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.1650273 ]
 [-0.94840193]
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[[-0.01800563 -0.30318027  0.26522406 ..., -0.23142647 -0.33990039
   0.26198232]
 [ 0.05891973  0.14856335  0.00540922 ..., -0.2212929   1.5780813
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 [-0.18469086 -0.24067259 -0.37808158 ...,  0.0894644  -0.60242527
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  -0.34196775]
 [ 0.03895352  0.08403243 -0.04494411 ...,  0.05354782  2.89388858
  -0.06914061]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16189842]
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[[-0.01805727 -0.30347883  0.26511563 ..., -0.23150278 -0.34045236
   0.26157435]
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   0.1167456 ]
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   0.96382241]
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 [-0.18466825 -0.24056457 -0.37779026 ...,  0.08950828 -0.60368858
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  -0.34286483]
 [ 0.03892287  0.08385181 -0.04526182 ...,  0.05347777  2.8938142
  -0.06955273]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16073825]
 [-0.94463415]
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[[-0.01821232 -0.3044222   0.26438382 ..., -0.2318135  -0.33955529
   0.26018226]
 [ 0.0587894   0.14780277  0.00484202 ..., -0.22152773  1.57871032
   0.11611807]
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 ..., 
 [-0.18470598 -0.24078757 -0.37799163 ...,  0.08943483 -0.60306931
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  -0.34261615]
 [ 0.03878651  0.0830608  -0.04614881 ...,  0.05321284  2.89419363
  -0.07071369]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16047205]
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[[-0.01824844 -0.30470757  0.26434932 ..., -0.23189443 -0.34153212
   0.25963805]
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 ..., 
 [-0.1846891  -0.24072569 -0.37807524 ...,  0.08947068 -0.60321314
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  -0.34283955]
 [ 0.0387607   0.0829151  -0.04636095 ...,  0.05316349  2.89425386
  -0.07112641]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16567379]
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[[-0.01812027 -0.30402652  0.26500538 ..., -0.23167532 -0.34455929
   0.26065988]
 [ 0.05889331  0.1483923   0.00530536 ..., -0.2213398   1.57797495
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 ..., 
 [-0.18461584 -0.24031776 -0.37768341 ...,  0.08959485 -0.60316842
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  -0.34300544]
 [ 0.03892123  0.08383376 -0.04540356 ...,  0.05345482  2.89392916
  -0.06979794]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.15729566]
 [-0.94103336]
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[[-0.01836859 -0.30537276  0.26369614 ..., -0.23210413 -0.33843759
   0.25895441]
 [ 0.05875386  0.14760352  0.00439356 ..., -0.2215813   1.58043002
   0.11548116]
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   0.95830851]
 ..., 
 [-0.18468709 -0.24071189 -0.37805905 ...,  0.08946429 -0.60190444
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 [-0.27636267 -0.18822218 -0.18616383 ..., -0.11975019 -0.15107486
  -0.34330713]
 [ 0.03887905  0.08358238 -0.0455143  ...,  0.05337457  2.89389633
  -0.07003644]]
Progress: 77.8% ... Training loss: 0.068 ... Validation loss: 0.147[[-0.16374629]
 [-0.94712707]
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[[-0.01815182 -0.30411769  0.2647965  ..., -0.2317261  -0.34293003
   0.26054554]
 [ 0.05876262  0.14765578  0.00444033 ..., -0.22156594  1.58037887
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 ..., 
 [-0.18465296 -0.24049069 -0.37779965 ...,  0.08953577 -0.60214677
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 [-0.27612908 -0.18684936 -0.1850342  ..., -0.11931723 -0.1543697
  -0.34138649]
 [ 0.03882606  0.08325209 -0.04569529 ...,  0.0532636   2.89400898
  -0.07054934]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16137921]
 [-0.94575768]
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[[-0.01837435 -0.30527955  0.26359992 ..., -0.23209857 -0.33909389
   0.25943821]
 [ 0.05871538  0.14742698  0.0042117  ..., -0.22163897  1.58099434
   0.11541571]
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 ..., 
 [-0.18469388 -0.24071145 -0.37805888 ...,  0.08946252 -0.60143014
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  -0.34107578]
 [ 0.03880863  0.08315907 -0.04587564 ...,  0.05321719  2.89400448
  -0.07045205]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16076229]
 [-0.94466883]
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[[-0.0185592  -0.30637504  0.26233398 ..., -0.23241766 -0.33760247
   0.25802267]
 [ 0.05869166  0.1472891   0.00404994 ..., -0.22168387  1.58105016
   0.11531343]
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   0.9604726 ]
 ..., 
 [-0.18470907 -0.24081493 -0.37837319 ...,  0.08944931 -0.60100044
  -0.31767683]
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  -0.34160883]
 [ 0.03871707  0.08262306 -0.04626865 ...,  0.05304611  2.89427099
  -0.07098536]]
Progress: 77.8% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.1640202 ]
 [-0.94757865]
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[[-0.01842138 -0.30557446  0.26345316 ..., -0.23215778 -0.34074482
   0.25964706]
 [ 0.05871134  0.14743084  0.00399403 ..., -0.22165048  1.58134859
   0.11554248]
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   0.96245281]
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 [-0.18459719 -0.2401915  -0.37791654 ...,  0.08964459 -0.6017463
  -0.3170954 ]
 [-0.27605667 -0.18645781 -0.18460042 ..., -0.11916781 -0.15539268
  -0.34044288]
 [ 0.03876564  0.08292553 -0.04595802 ...,  0.05313825  2.89409625
  -0.07072912]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16228798]
 [-0.94643692]
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[[-0.01845472 -0.30575115  0.26319997 ..., -0.23220835 -0.34051846
   0.25938632]
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 [ 0.03873597  0.08271851 -0.04610189 ...,  0.0530774   2.89419701
  -0.07109571]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16212431]
 [-0.94697032]
 [-1.18594948]
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 [-0.05556732]
 [ 2.60210469]
 [-0.04828293]
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[[-0.0184576  -0.30576127  0.26297006 ..., -0.23219643 -0.34075702
   0.25945732]
 [ 0.05866344  0.14715552  0.00376927 ..., -0.22173509  1.58165554
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  -0.33951581]
 [ 0.03876492  0.08288646 -0.04574594 ...,  0.05313241  2.89408001
  -0.07087359]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16639141]
 [-0.95052501]
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 [ 2.60112759]
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[[-0.01829433 -0.30485196  0.26383023 ..., -0.23189529 -0.34217568
   0.26068959]
 [ 0.05870346  0.14737011  0.00409961 ..., -0.2216644   1.58175476
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  -0.34005558]
 [ 0.0388134   0.0831696  -0.04553803 ...,  0.0532055   2.89399337
  -0.07026723]]
Progress: 77.8% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.15833384]
 [-0.94362948]
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 [-0.05278752]
 [ 2.60481898]
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[[-0.01863461 -0.306786    0.26194628 ..., -0.23255476 -0.33878998
   0.25882912]
 [ 0.05875801  0.14768618  0.00446996 ..., -0.22157277  1.58171361
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 [-0.18465893 -0.24053204 -0.37829431 ...,  0.08954048 -0.60139983
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  -0.34066563]
 [ 0.03874938  0.08282841 -0.04596053 ...,  0.05309188  2.89408449
  -0.07053697]]
Progress: 77.8% ... Training loss: 0.064 ... Validation loss: 0.146[[-0.1615427 ]
 [-0.94631919]
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 [ 2.60283366]
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[[-0.01856335 -0.30643075  0.2624105  ..., -0.23242389 -0.34085304
   0.25941899]
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  -0.33973153]
 [ 0.03877536  0.08297159 -0.04596764 ...,  0.0531453   2.8941522
  -0.07023117]]
Progress: 77.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16447299]
 [-0.94877252]
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[[-0.01858182 -0.30650291  0.26212635 ..., -0.2324618  -0.33892125
   0.25950056]
 [ 0.05871105  0.14743218  0.004196   ..., -0.2216547   1.58218448
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  -0.34114041]
 [ 0.03876142  0.08285067 -0.04599945 ...,  0.05311604  2.89410597
  -0.07025039]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.15942027]
 [-0.94407157]
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 [ 2.60568293]
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[[-0.01871415 -0.30721576  0.2612343  ..., -0.23268473 -0.33704184
   0.25884978]
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   0.1155941 ]
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 [-0.18449687 -0.23958437 -0.37798014 ...,  0.08985176 -0.60479789
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  -0.34132865]
 [ 0.03862652  0.08207689 -0.0465931  ...,  0.05286829  2.89431751
  -0.07118205]]
Progress: 77.9% ... Training loss: 0.064 ... Validation loss: 0.143[[-0.16377002]
 [-0.94798567]
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[[-0.01859657 -0.3065912   0.26161987 ..., -0.23247297 -0.33959474
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 ..., 
 [-0.18440518 -0.23906992 -0.37780725 ...,  0.09002853 -0.60716412
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  -0.3415199 ]
 [ 0.03861712  0.08202458 -0.04667199 ...,  0.05284809  2.8943255
  -0.07123231]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16281752]
 [-0.94723547]
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[[-0.0184634  -0.30581878  0.26246866 ..., -0.23222457 -0.33929932
   0.26089828]
 [ 0.05874324  0.14760643  0.00420482 ..., -0.22159138  1.58241006
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 ..., 
 [-0.18447556 -0.23947688 -0.37823278 ...,  0.0898942  -0.60586516
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  -0.34127735]
 [ 0.03868433  0.08240007 -0.04641925 ...,  0.05297023  2.89419028
  -0.07105829]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16210477]
 [-0.94652692]
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[[-0.01844196 -0.3056819   0.26261648 ..., -0.23220612 -0.33677627
   0.2616795 ]
 [ 0.05885204  0.14822547  0.0049475  ..., -0.22142598  1.58213001
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 ..., 
 [-0.18452847 -0.23977261 -0.37852632 ...,  0.08979823 -0.60514077
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  -0.34279746]
 [ 0.03873512  0.0826495  -0.0460532  ...,  0.05305444  2.89407204
  -0.07057461]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16414332]
 [-0.94832246]
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[[-0.01834869 -0.3051735   0.26303038 ..., -0.2320391  -0.33879711
   0.26209291]
 [ 0.05891903  0.14861354  0.00537245 ..., -0.22129052  1.58096401
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 ..., 
 [-0.18442032 -0.23919604 -0.37797107 ...,  0.08999295 -0.60701224
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  -0.34234494]
 [ 0.03866389  0.08223417 -0.04634889 ...,  0.05292448  2.89459086
  -0.07160789]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16242418]
 [-0.94674269]
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[[-0.01835224 -0.30520489  0.26316298 ..., -0.23205511 -0.33885092
   0.26179636]
 [ 0.05888796  0.14843344  0.00530061 ..., -0.22134852  1.58103525
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 [-0.18448766 -0.23960504 -0.37851953 ...,  0.08986665 -0.60626543
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  -0.34115766]
 [ 0.03865485  0.08218231 -0.0463469  ...,  0.05290466  2.89475347
  -0.0716964 ]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16082306]
 [-0.94517686]
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[[-0.01830227 -0.30495869  0.26329165 ..., -0.23197835 -0.33931826
   0.26244309]
 [ 0.05889779  0.14848939  0.00534057 ..., -0.22133261  1.58097251
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 ..., 
 [-0.18448628 -0.23959024 -0.37846848 ...,  0.08986226 -0.60665703 -0.31693   ]
 [-0.27599437 -0.18617317 -0.18427045 ..., -0.11900764 -0.15588169
  -0.3413511 ]
 [ 0.03860271  0.08182108 -0.04687296 ...,  0.05280221  2.89488938
  -0.07183714]]
Progress: 77.9% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16542066]
 [-0.94914769]
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[[-0.01797586 -0.30307085  0.26539171 ..., -0.23136559 -0.34306297
   0.26498622]
 [ 0.05888571  0.14841865  0.00527616 ..., -0.22135585  1.58113858
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 ..., 
 [-0.18451638 -0.23975821 -0.37872345 ...,  0.08980629 -0.60599331
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 [-0.27591937 -0.18574086 -0.1837344  ..., -0.11886472 -0.15691954
  -0.34074704]
 [ 0.03872748  0.0825588  -0.04626187 ...,  0.05303717  2.89472223
  -0.07095065]]
Progress: 77.9% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16031412]
 [-0.94448544]
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[[-0.01807036 -0.30362527  0.26482263 ..., -0.23153818 -0.3402856
   0.26423586]
 [ 0.05884806  0.14820253  0.00499263 ..., -0.2214207   1.58172326
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   0.96493147]
 ..., 
 [-0.18456988 -0.24005419 -0.37910853 ...,  0.0897076  -0.60533178
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  -0.34060628]
 [ 0.03873272  0.08257972 -0.04616257 ...,  0.05305523  2.89474671
  -0.07082183]]
Progress: 77.9% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16800563]
 [-0.95125706]
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   0.26566845]
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 [ 0.03893594  0.0837583  -0.04530202 ...,  0.05342938  2.89442168
  -0.06932483]]
Progress: 77.9% ... Training loss: 0.067 ... Validation loss: 0.141[[-0.15895292]
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 [ 0.03880573  0.08302358 -0.04564358 ...,  0.05319135  2.89462808
  -0.06991659]]
Progress: 77.9% ... Training loss: 0.064 ... Validation loss: 0.146[[-0.15793049]
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  -0.33957121]
 [ 0.03870344  0.08245094 -0.04618243 ...,  0.05299174  2.89488094
  -0.07078477]]
Progress: 77.9% ... Training loss: 0.066 ... Validation loss: 0.147[[-0.16654699]
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 [ 0.03896299  0.08396463 -0.04467148 ...,  0.0534827   2.89444348
  -0.06866881]]
Progress: 77.9% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16124785]
 [-0.94454168]
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[[-0.01858234 -0.30649559  0.26199477 ..., -0.23244629 -0.33606945
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  -0.34115276]
 [ 0.03896963  0.08397549 -0.04443683 ...,  0.0534916   2.89446896
  -0.06834237]]
Progress: 77.9% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.1602688 ]
 [-0.94320252]
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[[-0.01858219 -0.30652618  0.26204715 ..., -0.23245501 -0.33578088
   0.26069303]
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 [-0.18478271 -0.24122655 -0.38048989 ...,  0.08934091 -0.6019014
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  -0.34166275]
 [ 0.03891706  0.08367068 -0.04478895 ...,  0.0533904   2.89462886
  -0.06878966]]
Progress: 78.0% ... Training loss: 0.064 ... Validation loss: 0.145[[-0.16557601]
 [-0.94782338]
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[[-0.01845041 -0.30577351  0.26259099 ..., -0.23220687 -0.33702607
   0.26130582]
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 [ 0.03904789  0.08446187 -0.04416898 ...,  0.05364413  2.89445947
  -0.06806426]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.1660098 ]
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[[-0.01830874 -0.30493573  0.2634978  ..., -0.23194395 -0.33661305
   0.26278714]
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 [-0.18476353 -0.24113509 -0.3805649  ...,  0.08936781 -0.60163305
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 [ 0.03915604  0.08507895 -0.04379203 ...,  0.05382959  2.89435621
  -0.06722898]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16657852]
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[[-0.0180843  -0.30368284  0.26462191 ..., -0.23153451 -0.33658066
   0.2641467 ]
 [ 0.0587163   0.14743563  0.00403898 ..., -0.22165648  1.58241583
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 [-0.18472109 -0.24088716 -0.38045492 ...,  0.0894477  -0.6022439
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  -0.34344184]
 [ 0.03931143  0.08593975 -0.04300735 ...,  0.05410429  2.89410638
  -0.06597918]]
Progress: 78.0% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16585569]
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[[-0.01814002 -0.30399049  0.26466919 ..., -0.23162539 -0.33840096
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 [-0.18452963 -0.23982501 -0.3794866  ...,  0.08979872 -0.6051691
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 [ 0.03925491  0.08555484 -0.04320384 ...,  0.05400316  2.89437969
  -0.06599336]]
Progress: 78.0% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16337906]
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[[-0.01804972 -0.30336568  0.26535136 ..., -0.23144248 -0.33838355
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 [-0.18460736 -0.24025299 -0.37985629 ...,  0.08965915 -0.60414238
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 [ 0.03925407  0.08555165 -0.04343216 ...,  0.05400809  2.89446391
  -0.06605268]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16526391]
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[[-0.01791416 -0.30253555  0.26619253 ..., -0.23119456 -0.34123016
   0.26675539]
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 [-0.18463944 -0.24043126 -0.3799672  ...,  0.08960111 -0.60363573
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  -0.34390562]
 [ 0.03929309  0.08578793 -0.04316489 ...,  0.05407345  2.89425681
  -0.06584139]]
Progress: 78.0% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16205843]
 [-0.94573833]
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[[-0.01805437 -0.30326515  0.26560074 ..., -0.23146211 -0.33691833
   0.26578085]
 [ 0.05873194  0.14753002  0.00418779 ..., -0.22161161  1.58132312
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 ..., 
 [-0.18465476 -0.24050807 -0.38011108 ...,  0.08957292 -0.60361921
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 [ 0.03926723  0.08563961 -0.0432638  ...,  0.05402335  2.89427635
  -0.06593853]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16516176]
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[[-0.01775895 -0.30162725  0.26707565 ..., -0.23095116 -0.33897936
   0.26780939]
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 ..., 
 [-0.18461864 -0.24032118 -0.37997398 ...,  0.08963907 -0.60461571
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 [ 0.0392773   0.08569239 -0.04317741 ...,  0.05405034  2.89425478
  -0.0659065 ]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16345988]
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[[-0.01797956 -0.3029171   0.26581581 ..., -0.23135387 -0.33613748
   0.26599465]
 [ 0.05855159  0.14652318  0.0031524  ..., -0.22193521  1.58438947
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 [-0.18461707 -0.240316   -0.37994875 ...,  0.08964192 -0.60435515
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 [ 0.03926503  0.08561696 -0.04318927 ...,  0.05402471  2.89425492
  -0.0660568 ]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16582663]
 [-0.94853848]
 [-1.1906922 ]
 [-0.76986466]
 [-0.05670865]
 [ 2.60099831]
 [-0.04925955]
 [-1.08753965]
 [-0.52371428]
 [ 1.01272897]
 [-0.09548435]
 [ 0.14138459]
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 [ 0.87369764]
 [-0.83688012]
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 [ 0.13599369]
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 [ 4.46932523]
 [-0.94849807]
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 [ 0.3829581 ]
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 [ 4.27853998]
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[[-0.01787862 -0.30237727  0.26661912 ..., -0.231195   -0.33653094
   0.26707344]
 [ 0.05861947  0.14690545  0.00362947 ..., -0.2218362   1.58439574
   0.11535976]
 [-0.06201917  0.2550514   0.46438735 ...,  0.2328164  -0.30319619
   0.96547216]
 ..., 
 [-0.18457695 -0.24009223 -0.37974865 ...,  0.08971364 -0.60486424
  -0.31713529]
 [-0.27607359 -0.1865431  -0.1850622  ..., -0.11912614 -0.15561912
  -0.34353966]
 [ 0.03929569  0.08577142 -0.04295257 ...,  0.05407857  2.89425701
  -0.06569226]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16283824]
 [-0.94562586]
 [-1.18898247]
 [-0.76702108]
 [-0.05412364]
 [ 2.60253591]
 [-0.04628627]
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 [ 1.01443847]
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 [ 0.14405227]
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 [ 4.46889282]
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 [ 0.38536656]
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 [ 4.28316369]
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[[ -1.79206410e-02  -3.02604562e-01   2.66158227e-01 ...,  -2.31255712e-01
   -3.35235173e-01   2.66425892e-01]
 [  5.85097825e-02   1.46276785e-01   2.75946247e-03 ...,  -2.22029571e-01
    1.58643933e+00   1.14116021e-01]
 [ -6.20982948e-02   2.54537567e-01   4.63489056e-01 ...,   2.32703580e-01
   -3.01713456e-01   9.63440336e-01]
 ..., 
 [ -1.84728048e-01  -2.40942415e-01  -3.80389759e-01 ...,   8.94435096e-02
   -6.02892113e-01  -3.18066640e-01]
 [ -2.76105803e-01  -1.86731196e-01  -1.85112738e-01 ...,  -1.19185031e-01
   -1.55093517e-01  -3.43767038e-01]
 [  3.93100837e-02   8.58552870e-02  -4.29489708e-02 ...,   5.41059414e-02
    2.89419378e+00  -6.56476585e-02]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16513601]
 [-0.94763208]
 [-1.19002317]
 [-0.76850127]
 [-0.05560532]
 [ 2.60007351]
 [-0.04887305]
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 [ 4.46798521]
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 [ 0.38290544]
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 [ 4.28031305]
 [-1.89402357]]
[[ -1.79031262e-02  -3.02448889e-01   2.66657314e-01 ...,  -2.31220824e-01
   -3.36889399e-01   2.67811718e-01]
 [  5.84849163e-02   1.46141566e-01   2.59280717e-03 ...,  -2.22077625e-01
    1.58630917e+00   1.13930270e-01]
 [ -6.19048276e-02   2.55613896e-01   4.65033547e-01 ...,   2.33057993e-01
   -3.05467795e-01   9.65460885e-01]
 ..., 
 [ -1.84664703e-01  -2.40581729e-01  -3.80067118e-01 ...,   8.95541784e-02
   -6.03460740e-01  -3.17641200e-01]
 [ -2.76139346e-01  -1.86907524e-01  -1.85232512e-01 ...,  -1.19248290e-01
   -1.54962515e-01  -3.44025659e-01]
 [  3.93268771e-02   8.59550653e-02  -4.29076534e-02 ...,   5.41200717e-02
    2.89410323e+00  -6.54229965e-02]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16316318]
 [-0.94623227]
 [-1.19126242]
 [-0.76507142]
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 [ 2.60099387]
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 [-0.83547287]
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 [ 0.13967337]
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 [ 4.46758773]
 [-0.94579818]
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 [-0.30453771]
 [ 4.2825769 ]
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[[ -1.79695651e-02  -3.02725706e-01   2.66900941e-01 ...,  -2.31345056e-01
   -3.33511150e-01   2.67246207e-01]
 [  5.83913485e-02   1.45650893e-01   1.97249274e-03 ...,  -2.22236791e-01
    1.58811824e+00   1.13159564e-01]
 [ -6.17342664e-02   2.56564587e-01   4.65836071e-01 ...,   2.33371080e-01
   -3.05000583e-01   9.66123061e-01]
 ..., 
 [ -1.84703404e-01  -2.40784747e-01  -3.80061167e-01 ...,   8.94969070e-02
   -6.02911889e-01  -3.17980332e-01]
 [ -2.76184558e-01  -1.87147480e-01  -1.85100100e-01 ...,  -1.19345479e-01
   -1.52947546e-01  -3.44469491e-01]
 [  3.93722753e-02   8.62063792e-02  -4.26374486e-02 ...,   5.42103457e-02
    2.89407855e+00  -6.50831489e-02]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.144[[-0.16342715]
 [-0.94734636]
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 [-0.76755899]
 [-0.05470406]
 [ 2.60199496]
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 [ 0.87709754]
 [-0.83603013]
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 [ 4.46811075]
 [-0.94757208]
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 [ 0.38448724]
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 [ 4.28192525]
 [-1.89250784]]
[[ -1.82133534e-02  -3.04158043e-01   2.65128239e-01 ...,  -2.31772903e-01
   -3.31550570e-01   2.64540806e-01]
 [  5.84295783e-02   1.45858959e-01   2.07852698e-03 ...,  -2.22157263e-01
    1.58888570e+00   1.13271335e-01]
 [ -6.18998023e-02   2.55493311e-01   4.65175666e-01 ...,   2.33097606e-01
   -3.00309016e-01   9.64889110e-01]
 ..., 
 [ -1.84733337e-01  -2.40965350e-01  -3.80321463e-01 ...,   8.94459181e-02
   -6.02166898e-01  -3.18461072e-01]
 [ -2.76066338e-01  -1.86504823e-01  -1.84678114e-01 ...,  -1.19129906e-01
   -1.53996512e-01  -3.43950201e-01]
 [  3.94290405e-02   8.64809362e-02  -4.21497557e-02 ...,   5.43111401e-02
    2.89402659e+00  -6.43288517e-02]]
Progress: 78.0% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16221096]
 [-0.94571096]
 [-1.18948012]
 [-0.7659207 ]
 [-0.05323758]
 [ 2.60167893]
 [-0.0468759 ]
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 [ 4.46803188]
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 [ 0.3851708 ]
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 [ 4.28361448]
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[[ -1.81998932e-02  -3.04116015e-01   2.65300947e-01 ...,  -2.31751072e-01
   -3.30071541e-01   2.64947326e-01]
 [  5.84000936e-02   1.45699802e-01   1.91961783e-03 ...,  -2.22210591e-01
    1.58883699e+00   1.13105378e-01]
 [ -6.18121216e-02   2.55874482e-01   4.65594001e-01 ...,   2.33252251e-01
   -2.99330357e-01   9.64978489e-01]
 ..., 
 [ -1.84753112e-01  -2.41080157e-01  -3.80352642e-01 ...,   8.94097895e-02
   -6.02017729e-01  -3.18586525e-01]
 [ -2.75930393e-01  -1.85719677e-01  -1.83807879e-01 ...,  -1.18879714e-01
   -1.56567665e-01  -3.42674168e-01]
 [  3.94702775e-02   8.67264902e-02  -4.20428567e-02 ...,   5.43953915e-02
    2.89393858e+00  -6.35168332e-02]]
Progress: 78.1% ... Training loss: 0.062 ... Validation loss: 0.144[[-0.16601027]
 [-0.94877285]
 [-1.19059063]
 [-0.77100911]
 [-0.05701892]
 [ 2.5998675 ]
 [-0.05017123]
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 [ 1.01266046]
 [-0.09576896]
 [ 0.14260245]
 [-0.10552916]
 [-0.98641525]
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 [ 0.87481005]
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 [-0.34931553]
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 [ 0.3833623 ]
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[[ -1.81886437e-02  -3.04042097e-01   2.65249538e-01 ...,  -2.31707147e-01
   -3.30660208e-01   2.65494666e-01]
 [  5.83831258e-02   1.45597219e-01   1.69251537e-03 ...,  -2.22241893e-01
    1.58943094e+00   1.12794733e-01]
 [ -6.17793747e-02   2.55956546e-01   4.65981759e-01 ...,   2.33293493e-01
   -3.02005664e-01   9.65900537e-01]
 ..., 
 [ -1.84690101e-01  -2.40722361e-01  -3.80056139e-01 ...,   8.95287815e-02
   -6.04070499e-01  -3.17705087e-01]
 [ -2.76026653e-01  -1.86240906e-01  -1.84426044e-01 ...,  -1.19047512e-01
   -1.55567876e-01  -3.43005868e-01]
 [  3.95923054e-02   8.74367116e-02  -4.14104374e-02 ...,   5.46150507e-02
    2.89376877e+00  -6.28918797e-02]]
Progress: 78.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16225974]
 [-0.94539198]
 [-1.18724274]
 [-0.76792399]
 [-0.05352657]
 [ 2.60285349]
 [-0.04730785]
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 [ 1.01432302]
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 [ 0.14599701]
 [-0.10181089]
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 [ 0.87858227]
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 [ 0.14075194]
 [-0.34632857]
 [ 4.46858383]
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 [ 0.38611386]
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 [ 4.28436968]
 [-1.89273545]]
[[ -1.84434228e-02  -3.05459638e-01   2.63841386e-01 ...,  -2.32162016e-01
   -3.27520797e-01   2.63832490e-01]
 [  5.82875972e-02   1.45047237e-01   1.07457500e-03 ...,  -2.22411884e-01
    1.59102998e+00   1.11729198e-01]
 [ -6.19427619e-02   2.55016353e-01   4.64285519e-01 ...,   2.33001295e-01
   -2.98673792e-01   9.63007748e-01]
 ..., 
 [ -1.84772423e-01  -2.41182291e-01  -3.80619993e-01 ...,   8.93855201e-02
   -6.02748338e-01  -3.18310573e-01]
 [ -2.75907466e-01  -1.85578521e-01  -1.83950706e-01 ...,  -1.18826746e-01
   -1.56432039e-01  -3.42318446e-01]
 [  3.94907074e-02   8.68777812e-02  -4.18595825e-02 ...,   5.44270292e-02
    2.89397260e+00  -6.35420473e-02]]
Progress: 78.1% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.1634216 ]
 [-0.94628233]
 [-1.18601073]
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 [-0.05410703]
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 [ 4.46903597]
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[[ -1.83542267e-02  -3.04953220e-01   2.64226743e-01 ...,  -2.31985609e-01
   -3.26738762e-01   2.64409744e-01]
 [  5.83460560e-02   1.45392262e-01   1.37423182e-03 ...,  -2.22303812e-01
    1.59056659e+00   1.12186843e-01]
 [ -6.20791578e-02   2.54221194e-01   4.63602571e-01 ...,   2.32759250e-01
   -2.97492940e-01   9.62269069e-01]
 ..., 
 [ -1.84756794e-01  -2.41106302e-01  -3.80506743e-01 ...,   8.94104437e-02
   -6.03304010e-01  -3.17943351e-01]
 [ -2.75912947e-01  -1.85605202e-01  -1.84056681e-01 ...,  -1.18832115e-01
   -1.56313129e-01  -3.42550190e-01]
 [  3.95986546e-02   8.75021640e-02  -4.12907313e-02 ...,   5.46268487e-02
    2.89377204e+00  -6.31010641e-02]]
Progress: 78.1% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16173123]
 [-0.94517761]
 [-1.18754349]
 [-0.76720574]
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 [ 2.60443025]
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 [ 4.28407194]
 [-1.89249618]]
[[ -1.85329307e-02  -3.05910948e-01   2.63880132e-01 ...,  -2.32301932e-01
   -3.25073933e-01   2.63021423e-01]
 [  5.84210351e-02   1.45832557e-01   1.72173288e-03 ...,  -2.22172850e-01
    1.59027990e+00   1.12696617e-01]
 [ -6.20556265e-02   2.54421072e-01   4.63354781e-01 ...,   2.32817751e-01
   -2.98075845e-01   9.61893359e-01]
 ..., 
 [ -1.84684570e-01  -2.40683158e-01  -3.80080328e-01 ...,   8.95396742e-02
   -6.03213429e-01  -3.17662563e-01]
 [ -2.75937393e-01  -1.85770843e-01  -1.84027681e-01 ...,  -1.18877224e-01
   -1.55613982e-01  -3.42931026e-01]
 [  3.96502696e-02   8.78066323e-02  -4.07761425e-02 ...,   5.47239840e-02
    2.89360888e+00  -6.26827795e-02]]
Progress: 78.1% ... Training loss: 0.064 ... Validation loss: 0.145[[-0.16851735]
 [-0.95115871]
 [-1.1932877 ]
 [-0.7733894 ]
 [-0.05838514]
 [ 2.60157868]
 [-0.05245267]
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[[ -1.82929291e-02  -3.04465552e-01   2.65405011e-01 ...,  -2.31861016e-01
   -3.28034330e-01   2.65211805e-01]
 [  5.84607777e-02   1.46064944e-01   2.00277879e-03 ...,  -2.22105460e-01
    1.58995373e+00   1.13100736e-01]
 [ -6.20283303e-02   2.54587218e-01   4.63659428e-01 ...,   2.32899767e-01
   -3.00167370e-01   9.62776560e-01]
 ..., 
 [ -1.84650824e-01  -2.40504490e-01  -3.80111545e-01 ...,   8.96010952e-02
   -6.03614980e-01  -3.17614232e-01]
 [ -2.75756404e-01  -1.84762979e-01  -1.82991271e-01 ...,  -1.18563916e-01
   -1.57464094e-01  -3.41896398e-01]
 [  3.97444837e-02   8.83712900e-02  -4.02268055e-02 ...,   5.49094245e-02
    2.89353960e+00  -6.22324583e-02]]
Progress: 78.1% ... Training loss: 0.065 ... Validation loss: 0.141[[-0.16341435]
 [-0.94591745]
 [-1.18933817]
 [-0.76759026]
 [-0.05338952]
 [ 2.60266565]
 [-0.04779532]
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 [ 1.015039  ]
 [-0.09222846]
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 [-0.10313483]
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 [-0.34884444]
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[[ -1.83468380e-02  -3.04762775e-01   2.65405682e-01 ...,  -2.31955363e-01
   -3.26512395e-01   2.65010907e-01]
 [  5.83870627e-02   1.45654313e-01   1.65078963e-03 ...,  -2.22240799e-01
    1.59029222e+00   1.12280039e-01]
 [ -6.19566832e-02   2.54965754e-01   4.63512384e-01 ...,   2.33053886e-01
   -3.00606009e-01   9.61884923e-01]
 ..., 
 [ -1.84718393e-01  -2.40882995e-01  -3.80299734e-01 ...,   8.94794694e-02
   -6.03340475e-01  -3.17852853e-01]
 [ -2.75821553e-01  -1.85109515e-01  -1.83462492e-01 ...,  -1.18677528e-01
   -1.56223985e-01  -3.42554384e-01]
 [  3.98119772e-02   8.87451279e-02  -3.97324824e-02 ...,   5.50272687e-02
    2.89327434e+00  -6.13829613e-02]]
Progress: 78.1% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16780468]
 [-0.94976265]
 [-1.19292491]
 [-0.77184986]
 [-0.05710935]
 [ 2.60120222]
 [-0.05162801]
 [-1.09042352]
 [-0.52578008]
 [ 1.01199336]
 [-0.09675704]
 [ 0.14033884]
 [-0.10674883]
 [-0.98592605]
 [-0.29708635]
 [ 0.87109774]
 [-0.83990718]
 [-0.79410912]
 [-0.61834102]
 [ 0.13665217]
 [-0.35321833]
 [ 4.46902728]
 [-0.94935161]
 [-1.64876453]
 [ 0.38149418]
 [-0.30949315]
 [ 4.27420055]
 [-1.89506609]]
[[ -1.81604927e-02  -3.03725363e-01   2.66340327e-01 ...,  -2.31616295e-01
   -3.29406102e-01   2.66585225e-01]
 [  5.84337478e-02   1.45919692e-01   1.87326915e-03 ...,  -2.22157720e-01
    1.58993779e+00   1.12484009e-01]
 [ -6.19644453e-02   2.54882720e-01   4.63446476e-01 ...,   2.33063515e-01
   -3.02253691e-01   9.62350420e-01]
 ..., 
 [ -1.84699612e-01  -2.40768029e-01  -3.80088884e-01 ...,   8.95120837e-02
   -6.04252678e-01  -3.17619884e-01]
 [ -2.75703299e-01  -1.84492844e-01  -1.83011604e-01 ...,  -1.18483441e-01
   -1.56809281e-01  -3.42098474e-01]
 [  3.96789145e-02   8.79896479e-02  -4.03422964e-02 ...,   5.47726275e-02
    2.89342525e+00  -6.26079483e-02]]
Progress: 78.1% ... Training loss: 0.064 ... Validation loss: 0.141[[-0.16082582]
 [-0.94475235]
 [-1.18816146]
 [-0.76533675]
 [-0.05150738]
 [ 2.60431448]
 [-0.04579151]
 [-1.08514407]
 [-0.52022616]
 [ 1.01571606]
 [-0.09087858]
 [ 0.14593868]
 [-0.10047344]
 [-0.9814917 ]
 [-0.29143569]
 [ 0.87767736]
 [-0.83359615]
 [-0.78903087]
 [-0.61357316]
 [ 0.14213477]
 [-0.34788345]
 [ 4.47017706]
 [-0.94349371]
 [-1.64239638]
 [ 0.38611771]
 [-0.30366852]
 [ 4.28480711]
 [-1.89218035]]
[[ -1.83996094e-02  -3.04976316e-01   2.65199489e-01 ...,  -2.32041862e-01
   -3.26162960e-01   2.65386814e-01]
 [  5.83639027e-02   1.45570789e-01   1.76029812e-03 ...,  -2.22282826e-01
    1.59046562e+00   1.12279780e-01]
 [ -6.20225648e-02   2.54469807e-01   4.62483314e-01 ...,   2.32966859e-01
   -3.00060915e-01   9.60178400e-01]
 ..., 
 [ -1.84753108e-01  -2.41057634e-01  -3.80428756e-01 ...,   8.94202464e-02
   -6.03451704e-01  -3.18271783e-01]
 [ -2.75745809e-01  -1.84731961e-01  -1.83354539e-01 ...,  -1.18552165e-01
   -1.56146645e-01  -3.42506288e-01]
 [  3.96195567e-02   8.76721984e-02  -4.07011119e-02 ...,   5.46663807e-02
    2.89355004e+00  -6.34910878e-02]]
Progress: 78.1% ... Training loss: 0.064 ... Validation loss: 0.146[[-0.16743114]
 [-0.95040664]
 [-1.19245583]
 [-0.77228113]
 [-0.05715099]
 [ 2.60224741]
 [-0.05219453]
 [-1.09078736]
 [-0.526214  ]
 [ 1.01201412]
 [-0.0961864 ]
 [ 0.14008727]
 [-0.10775201]
 [-0.98641796]
 [-0.29699479]
 [ 0.87074862]
 [-0.8396262 ]
 [-0.79411729]
 [-0.61822422]
 [ 0.13578857]
 [-0.3540913 ]
 [ 4.468289  ]
 [-0.9492035 ]
 [-1.64895599]
 [ 0.38112161]
 [-0.30932729]
 [ 4.27372145]
 [-1.89525677]]
[[ -1.81009829e-02  -3.03322404e-01   2.66652533e-01 ...,  -2.31497203e-01
   -3.30352035e-01   2.67462483e-01]
 [  5.83603693e-02   1.45544662e-01   1.67547968e-03 ...,  -2.22288455e-01
    1.59072103e+00   1.12079036e-01]
 [ -6.20158339e-02   2.54556286e-01   4.62659517e-01 ...,   2.32996919e-01
   -3.01967885e-01   9.61160969e-01]
 ..., 
 [ -1.84672026e-01  -2.40640744e-01  -3.80109272e-01 ...,   8.95648958e-02
   -6.04839905e-01  -3.17789189e-01]
 [ -2.75523409e-01  -1.83493352e-01  -1.82430866e-01 ...,  -1.18147160e-01
   -1.58464167e-01  -3.40794455e-01]
 [  3.96209388e-02   8.76594674e-02  -4.06644726e-02 ...,   5.46622631e-02
    2.89362724e+00  -6.36888515e-02]]
Progress: 78.1% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16649533]
 [-0.94999821]
 [-1.19210245]
 [-0.77050988]
 [-0.05648079]
 [ 2.60308024]
 [-0.05088157]
 [-1.08944625]
 [-0.52571844]
 [ 1.01178593]
 [-0.09490828]
 [ 0.14097096]
 [-0.1064847 ]
 [-0.98631073]
 [-0.2961024 ]
 [ 0.87188524]
 [-0.83841172]
 [-0.79383194]
 [-0.61802427]
 [ 0.13694685]
 [-0.35339825]
 [ 4.46819117]
 [-0.94818686]
 [-1.64772844]
 [ 0.38130747]
 [-0.3075788 ]
 [ 4.2756903 ]
 [-1.89454151]]
[[ -1.81651032e-02  -3.03576233e-01   2.66361804e-01 ...,  -2.31637471e-01
   -3.29373759e-01   2.66648923e-01]
 [  5.83814796e-02   1.45656947e-01   1.72634305e-03 ...,  -2.22254665e-01
    1.59064558e+00   1.12158143e-01]
 [ -6.19161399e-02   2.55071215e-01   4.63577628e-01 ...,   2.33149814e-01
   -3.04481596e-01   9.60952297e-01]
 ..., 
 [ -1.84749109e-01  -2.41065164e-01  -3.80554821e-01 ...,   8.94263912e-02
   -6.03852741e-01  -3.18222883e-01]
 [ -2.75524460e-01  -1.83473965e-01  -1.82421895e-01 ...,  -1.18163011e-01
   -1.57830426e-01  -3.40666702e-01]
 [  3.95036190e-02   8.70365929e-02  -4.14152950e-02 ...,   5.44474337e-02
    2.89382582e+00  -6.48749763e-02]]
Progress: 78.1% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.1602543 ]
 [-0.94553392]
 [-1.18810221]
 [-0.76513325]
 [-0.05193218]
 [ 2.60506079]
 [-0.04701695]
 [-1.08431312]
 [-0.52156357]
 [ 1.01422919]
 [-0.08965431]
 [ 0.14607279]
 [-0.10251086]
 [-0.98466204]
 [-0.29051228]
 [ 0.87785941]
 [-0.8322231 ]
 [-0.78993884]
 [-0.61315411]
 [ 0.14187002]
 [-0.34883407]
 [ 4.46823966]
 [-0.94463808]
 [-1.64130952]
 [ 0.38482633]
 [-0.30311922]
 [ 4.28619811]
 [-1.89304216]]
[[ -1.83699813e-02  -3.04761639e-01   2.65417616e-01 ...,  -2.32013310e-01
   -3.31447851e-01   2.65827410e-01]
 [  5.84567067e-02   1.46083279e-01   1.97910919e-03 ...,  -2.22118836e-01
    1.59048286e+00   1.12648824e-01]
 [ -6.18397738e-02   2.55386668e-01   4.63669589e-01 ...,   2.33276933e-01
   -3.08018127e-01   9.60016237e-01]
 ..., 
 [ -1.84685171e-01  -2.40716576e-01  -3.80314456e-01 ...,   8.95435765e-02
   -6.03999224e-01  -3.17790478e-01]
 [ -2.75521499e-01  -1.83456905e-01  -1.82303882e-01 ...,  -1.18162137e-01
   -1.58221094e-01  -3.40625557e-01]
 [  3.94078570e-02   8.65083408e-02  -4.19282858e-02 ...,   5.42735945e-02
    2.89395423e+00  -6.56564991e-02]]
Progress: 78.1% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.16139412]
 [-0.94623235]
 [-1.18759677]
 [-0.76738672]
 [-0.05417005]
 [ 2.60633997]
 [-0.04768093]
 [-1.08810811]
 [-0.52118207]
 [ 1.01419054]
 [-0.09080589]
 [ 0.14431556]
 [-0.10376483]
 [-0.98385659]
 [-0.29115666]
 [ 0.87576248]
 [-0.83288177]
 [-0.78996953]
 [-0.61363663]
 [ 0.1402031 ]
 [-0.35004858]
 [ 4.46895705]
 [-0.94586247]
 [-1.64437263]
 [ 0.38465379]
 [-0.3039702 ]
 [ 4.28487231]
 [-1.89226127]]
[[ -1.83684726e-02  -3.04831502e-01   2.65125970e-01 ...,  -2.32011295e-01
   -3.31866037e-01   2.64948511e-01]
 [  5.83562340e-02   1.45500511e-01   1.18910925e-03 ...,  -2.22291106e-01
    1.59228302e+00   1.11291323e-01]
 [ -6.21948859e-02   2.53388871e-01   4.61530363e-01 ...,   2.32669447e-01
   -3.03258631e-01   9.57080250e-01]
 ..., 
 [ -1.84616344e-01  -2.40343862e-01  -3.80149353e-01 ...,   8.96696104e-02
   -6.05391991e-01  -3.17440653e-01]
 [ -2.75566525e-01  -1.83701736e-01  -1.82631576e-01 ...,  -1.18251391e-01
   -1.57437214e-01  -3.41128813e-01]
 [  3.94527913e-02   8.67480718e-02  -4.14427375e-02 ...,   5.43483852e-02
    2.89385041e+00  -6.56284083e-02]]
Progress: 78.1% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.1620914 ]
 [-0.94714635]
 [-1.1888717 ]
 [-0.76733561]
 [-0.05468698]
 [ 2.60594869]
 [-0.04843948]
 [-1.08828434]
 [-0.52215999]
 [ 1.01287426]
 [-0.09156655]
 [ 0.14334549]
 [-0.10457245]
 [-0.98439856]
 [-0.29234285]
 [ 0.87424524]
 [-0.83369044]
 [-0.79122116]
 [-0.61502488]
 [ 0.1397917 ]
 [-0.35017478]
 [ 4.46877289]
 [-0.94620821]
 [-1.64440548]
 [ 0.38403597]
 [-0.30526879]
 [ 4.28435115]
 [-1.89269391]]
[[ -1.83411333e-02  -3.04702000e-01   2.65128030e-01 ...,  -2.31957461e-01
   -3.33710400e-01   2.65081798e-01]
 [  5.82561059e-02   1.44937027e-01   6.01022490e-04 ...,  -2.22468556e-01
    1.59300760e+00   1.10503315e-01]
 [ -6.20924957e-02   2.54039465e-01   4.62029619e-01 ...,   2.32871508e-01
   -3.04340247e-01   9.57916188e-01]
 ..., 
 [ -1.84519724e-01  -2.39814638e-01  -3.79568182e-01 ...,   8.98523351e-02
   -6.06859812e-01  -3.16850974e-01]
 [ -2.75587317e-01  -1.83825336e-01  -1.82954498e-01 ...,  -1.18293454e-01
   -1.58206894e-01  -3.41384681e-01]
 [  3.94082167e-02   8.64988482e-02  -4.18153650e-02 ...,   5.42643541e-02
    2.89412505e+00  -6.60068274e-02]]
Progress: 78.1% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.15871464]
 [-0.94413289]
 [-1.18681958]
 [-0.76440756]
 [-0.05070163]
 [ 2.60530329]
 [-0.04631996]
 [-1.08443862]
 [-0.5197064 ]
 [ 1.01548601]
 [-0.08793481]
 [ 0.14666555]
 [-0.10157265]
 [-0.98420592]
 [-0.28916348]
 [ 0.87841282]
 [-0.83042717]
 [-0.78805028]
 [-0.61161712]
 [ 0.14318069]
 [-0.34641616]
 [ 4.46958526]
 [-0.94419284]
 [-1.63892722]
 [ 0.38634703]
 [-0.3029542 ]
 [ 4.289958  ]
 [-1.89289154]]
[[ -1.84413772e-02  -3.05280294e-01   2.64231248e-01 ...,  -2.32125449e-01
   -3.33054370e-01   2.64731745e-01]
 [  5.82561059e-02   1.44937027e-01   6.01022490e-04 ...,  -2.22468556e-01
    1.59300760e+00   1.10503315e-01]
 [ -6.18393074e-02   2.55566047e-01   4.63555534e-01 ...,   2.33346636e-01
   -3.05171678e-01   9.59276119e-01]
 ..., 
 [ -1.84534913e-01  -2.39878572e-01  -3.79552774e-01 ...,   8.98279965e-02
   -6.06564086e-01  -3.16799012e-01]
 [ -2.75685423e-01  -1.84392294e-01  -1.83631126e-01 ...,  -1.18474889e-01
   -1.56938951e-01  -3.42221952e-01]
 [  3.93734481e-02   8.62793003e-02  -4.20798630e-02 ...,   5.42053620e-02
    2.89405702e+00  -6.61274539e-02]]
Progress: 78.1% ... Training loss: 0.064 ... Validation loss: 0.145[[-0.16430894]
 [-0.94857267]
 [-1.18939248]
 [-0.76963405]
 [-0.05552327]
 [ 2.60257369]
 [-0.05150874]
 [-1.08948276]
 [-0.52421533]
 [ 1.01304729]
 [-0.09213658]
 [ 0.14175003]
 [-0.10727613]
 [-0.9882057 ]
 [-0.29411726]
 [ 0.87358921]
 [-0.83531992]
 [-0.79157862]
 [-0.61496213]
 [ 0.1381121 ]
 [-0.35184272]
 [ 4.46871695]
 [-0.94877507]
 [-1.64427606]
 [ 0.38215743]
 [-0.30740605]
 [ 4.28124387]
 [-1.89533487]]
[[ -1.82148929e-02  -3.04003608e-01   2.65785371e-01 ...,  -2.31705281e-01
   -3.36205966e-01   2.66818072e-01]
 [  5.83449091e-02   1.45461518e-01   1.15511716e-03 ...,  -2.22295934e-01
    1.59178625e+00   1.11361976e-01]
 [ -6.18693728e-02   2.55288149e-01   4.63857805e-01 ...,   2.33307818e-01
   -3.06482157e-01   9.60169988e-01]
 ..., 
 [ -1.84487482e-01  -2.39646070e-01  -3.79369822e-01 ...,   8.99144565e-02
   -6.07586854e-01  -3.16542137e-01]
 [ -2.75683362e-01  -1.84393803e-01  -1.83909777e-01 ...,  -1.18473965e-01
   -1.57219107e-01  -3.42475632e-01]
 [  3.95556437e-02   8.73686664e-02  -4.12692331e-02 ...,   5.45406149e-02
    2.89370570e+00  -6.49499318e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16220174]
 [-0.94679789]
 [-1.18641113]
 [-0.76792183]
 [-0.05384917]
 [ 2.60411622]
 [-0.04985072]
 [-1.08824923]
 [-0.52154903]
 [ 1.01558757]
 [-0.09062876]
 [ 0.14386564]
 [-0.10540025]
 [-0.98684246]
 [-0.29170802]
 [ 0.87626585]
 [-0.83264879]
 [-0.78868801]
 [-0.61242294]
 [ 0.13997272]
 [-0.34961706]
 [ 4.46866435]
 [-0.94784411]
 [-1.64275731]
 [ 0.38401385]
 [-0.30527042]
 [ 4.2846346 ]
 [-1.89458382]]
[[ -1.81998747e-02  -3.03874864e-01   2.65777332e-01 ...,  -2.31687880e-01
   -3.34518470e-01   2.67136976e-01]
 [  5.84115344e-02   1.45877740e-01   1.58068322e-03 ...,  -2.22186548e-01
    1.59195150e+00   1.12214478e-01]
 [ -6.19797247e-02   2.54740750e-01   4.62930730e-01 ...,   2.33072649e-01
   -3.02927097e-01   9.59049762e-01]
 ..., 
 [ -1.84466079e-01  -2.39534684e-01  -3.79259248e-01 ...,   8.99577413e-02
   -6.08095153e-01  -3.16273224e-01]
 [ -2.75774514e-01  -1.84903066e-01  -1.84475658e-01 ...,  -1.18647899e-01
   -1.55520520e-01  -3.43494555e-01]
 [  3.95672107e-02   8.74321810e-02  -4.13217966e-02 ...,   5.45522836e-02
    2.89361905e+00  -6.46612535e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16471663]
 [-0.94849189]
 [-1.18793906]
 [-0.76971422]
 [-0.0558913 ]
 [ 2.60289577]
 [-0.0518884 ]
 [-1.08950008]
 [-0.52346621]
 [ 1.01486279]
 [-0.09246025]
 [ 0.14198359]
 [-0.10758011]
 [-0.98853753]
 [-0.29390617]
 [ 0.87359499]
 [-0.83475355]
 [-0.78991979]
 [-0.61438271]
 [ 0.13808523]
 [-0.35176131]
 [ 4.4680054 ]
 [-0.94918653]
 [-1.64461197]
 [ 0.38220371]
 [-0.30654562]
 [ 4.28160984]
 [-1.89605316]]
[[ -1.80001003e-02  -3.02761617e-01   2.66777187e-01 ...,  -2.31321358e-01
   -3.37112191e-01   2.69048229e-01]
 [  5.84175419e-02   1.45908062e-01   1.58688430e-03 ...,  -2.22177402e-01
    1.59197048e+00   1.12197002e-01]
 [ -6.19158895e-02   2.55057477e-01   4.63416549e-01 ...,   2.33194622e-01
   -3.04795389e-01   9.60155513e-01]
 ..., 
 [ -1.84508054e-01  -2.39795227e-01  -3.79568719e-01 ...,   8.98885362e-02
   -6.07937079e-01  -3.16699043e-01]
 [ -2.75815650e-01  -1.85156991e-01  -1.84711343e-01 ...,  -1.18725646e-01
   -1.54207226e-01  -3.43841038e-01]
 [  3.95547425e-02   8.73395294e-02  -4.13985949e-02 ...,   5.45282076e-02
    2.89360518e+00  -6.46834048e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16276136]
 [-0.94774026]
 [-1.18690492]
 [-0.76773059]
 [-0.05455303]
 [ 2.60341098]
 [-0.05051591]
 [-1.08776092]
 [-0.52240637]
 [ 1.0152277 ]
 [-0.09085004]
 [ 0.14357103]
 [-0.10588891]
 [-0.98724218]
 [-0.29300597]
 [ 0.87535701]
 [-0.83304208]
 [-0.78782345]
 [-0.61361292]
 [ 0.13981235]
 [-0.35023511]
 [ 4.46920439]
 [-0.94696587]
 [-1.64252187]
 [ 0.38386586]
 [-0.30569154]
 [ 4.28443841]
 [-1.89546394]]
[[ -1.81949668e-02  -3.03796829e-01   2.65663959e-01 ...,  -2.31652876e-01
   -3.33369120e-01   2.67964401e-01]
 [  5.84698945e-02   1.46153491e-01   1.90393918e-03 ...,  -2.22079499e-01
    1.59189684e+00   1.12873794e-01]
 [ -6.18076677e-02   2.55642455e-01   4.63521541e-01 ...,   2.33400704e-01
   -3.03674945e-01   9.60517291e-01]
 ..., 
 [ -1.84548646e-01  -2.40031101e-01  -3.79843891e-01 ...,   8.98157082e-02
   -6.07590277e-01  -3.16966798e-01]
 [ -2.75881901e-01  -1.85472584e-01  -1.85024962e-01 ...,  -1.18840179e-01
   -1.52842466e-01  -3.44483221e-01]
 [  3.95209709e-02   8.71495463e-02  -4.15230418e-02 ...,   5.44659147e-02
    2.89362855e+00  -6.47999904e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16587687]
 [-0.95115221]
 [-1.18815418]
 [-0.77062857]
 [-0.0573153 ]
 [ 2.60128904]
 [-0.05406799]
 [-1.08977775]
 [-0.52576924]
 [ 1.0136548 ]
 [-0.09317   ]
 [ 0.14066668]
 [-0.10973761]
 [-0.99032953]
 [-0.29641632]
 [ 0.87262583]
 [-0.83573162]
 [-0.78967351]
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 [ 0.13682722]
 [-0.35356199]
 [ 4.46789453]
 [-0.95011381]
 [-1.64469891]
 [ 0.38112438]
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 [ 4.27828129]
 [-1.89788808]]
[[ -1.80743150e-02  -3.03066468e-01   2.66361697e-01 ...,  -2.31432390e-01
   -3.33555070e-01   2.69257372e-01]
 [  5.85394277e-02   1.46494857e-01   2.22914931e-03 ...,  -2.21949689e-01
    1.59166229e+00   1.13579272e-01]
 [ -6.16126010e-02   2.56583417e-01   4.64489995e-01 ...,   2.33754884e-01
   -3.03237752e-01   9.61989856e-01]
 ..., 
 [ -1.84450606e-01  -2.39451063e-01  -3.79270300e-01 ...,   9.00011974e-02
   -6.08507073e-01  -3.16329940e-01]
 [ -2.75732063e-01  -1.84628717e-01  -1.84413834e-01 ...,  -1.18572302e-01
   -1.54411691e-01  -3.43644209e-01]
 [  3.95126507e-02   8.70753824e-02  -4.15714132e-02 ...,   5.44491081e-02
    2.89362834e+00  -6.46234717e-02]]
Progress: 78.2% ... Training loss: 0.064 ... Validation loss: 0.139[[-0.15628789]
 [-0.94407745]
 [-1.18219367]
 [-0.76283175]
 [-0.04938371]
 [ 2.60590909]
 [-0.04664995]
 [-1.08304057]
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 [ 1.01902155]
 [-0.08539447]
 [ 0.14839928]
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 [-0.98515414]
 [-0.28798353]
 [ 0.88155702]
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 [ 0.14462756]
 [-0.34634417]
 [ 4.46997866]
 [-0.94248504]
 [-1.63646544]
 [ 0.38758834]
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 [ 4.29188079]
 [-1.89493518]]
[[ -1.83976157e-02  -3.04754608e-01   2.64791743e-01 ...,  -2.31989391e-01
   -3.28561215e-01   2.67290413e-01]
 [  5.85622068e-02   1.46636866e-01   2.34235305e-03 ...,  -2.21904348e-01
    1.59123115e+00   1.13864608e-01]
 [ -6.17008096e-02   2.55943746e-01   4.63185038e-01 ...,   2.33611853e-01
   -3.00055110e-01   9.59351679e-01]
 ..., 
 [ -1.84532825e-01  -2.39845943e-01  -3.79433991e-01 ...,   8.98651418e-02
   -6.07471673e-01  -3.16760191e-01]
 [ -2.75768625e-01  -1.84808818e-01  -1.84457546e-01 ...,  -1.18630057e-01
   -1.53439034e-01  -3.43755512e-01]
 [  3.94460271e-02   8.66873443e-02  -4.18364810e-02 ...,   5.43263547e-02
    2.89363578e+00  -6.47864675e-02]]
Progress: 78.2% ... Training loss: 0.068 ... Validation loss: 0.148[[-0.16420267]
 [-0.95003182]
 [-1.18889591]
 [-0.76914611]
 [-0.05560581]
 [ 2.60343958]
 [-0.05306372]
 [-1.08831183]
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 [ 1.01309761]
 [-0.09254168]
 [ 0.14161133]
 [-0.10921541]
 [-0.98976049]
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 [ 0.87339842]
 [-0.83509218]
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 [ 0.13793816]
 [-0.35329687]
 [ 4.46889852]
 [-0.94834348]
 [-1.64348178]
 [ 0.38205185]
 [-0.30758815]
 [ 4.27992728]
 [-1.89851876]]
[[ -1.81736123e-02  -3.03553414e-01   2.65984838e-01 ...,  -2.31569836e-01
   -3.31788340e-01   2.69437211e-01]
 [  5.85817734e-02   1.46757992e-01   2.36556646e-03 ...,  -2.21869109e-01
    1.59142343e+00   1.14000763e-01]
 [ -6.15942318e-02   2.56622280e-01   4.64476791e-01 ...,   2.33849166e-01
   -3.00893540e-01   9.62000667e-01]
 ..., 
 [ -1.84398234e-01  -2.39101227e-01  -3.78777014e-01 ...,   9.01208040e-02
   -6.09048411e-01  -3.15927948e-01]
 [ -2.75701971e-01  -1.84475260e-01  -1.84009866e-01 ...,  -1.18513367e-01
   -1.55689473e-01  -3.43646191e-01]
 [  3.95498184e-02   8.72834889e-02  -4.10863642e-02 ...,   5.45227184e-02
    2.89344139e+00  -6.35523509e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16226351]
 [-0.94839592]
 [-1.18845993]
 [-0.76681791]
 [-0.0535462 ]
 [ 2.60582919]
 [-0.05124325]
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 [ 1.01196328]
 [-0.0908759 ]
 [ 0.14306706]
 [-0.10822283]
 [-0.98872294]
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 [ 0.87490731]
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 [ 0.13937984]
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 [ 4.46781213]
 [-0.94670042]
 [-1.64326601]
 [ 0.38386211]
 [-0.30566708]
 [ 4.28324419]
 [-1.89734093]]
[[ -1.83198473e-02  -3.04431642e-01   2.65332184e-01 ...,  -2.31850377e-01
   -3.31760721e-01   2.67953557e-01]
 [  5.85641472e-02   1.46652836e-01   2.26489971e-03 ...,  -2.21902960e-01
    1.59147346e+00   1.13774113e-01]
 [ -6.17478549e-02   2.55690297e-01   4.63617527e-01 ...,   2.33563794e-01
   -3.00344467e-01   9.61574512e-01]
 ..., 
 [ -1.84432766e-01  -2.39321011e-01  -3.78660541e-01 ...,   9.00530374e-02
   -6.08253689e-01  -3.16500229e-01]
 [ -2.75667449e-01  -1.84280154e-01  -1.83721963e-01 ...,  -1.18447322e-01
   -1.56333752e-01  -3.43353074e-01]
 [  3.94805267e-02   8.68330598e-02  -4.13368241e-02 ...,   5.43841859e-02
    2.89371094e+00  -6.41781359e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16101426]
 [-0.94691014]
 [-1.18679495]
 [-0.76592182]
 [-0.0522133 ]
 [ 2.60691328]
 [-0.04972341]
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 [ 1.01381931]
 [-0.08986341]
 [ 0.14517619]
 [-0.10589503]
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 [-0.29105814]
 [ 0.87722722]
 [-0.83142172]
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 [ 0.14122423]
 [-0.35019648]
 [ 4.4688126 ]
 [-0.9464477 ]
 [-1.64229687]
 [ 0.38484922]
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 [ 4.28601453]
 [-1.89765561]]
[[ -1.83806372e-02  -3.04786575e-01   2.64909287e-01 ...,  -2.31956142e-01
   -3.31208512e-01   2.68200098e-01]
 [  5.85498568e-02   1.46570603e-01   2.09367083e-03 ...,  -2.21929437e-01
    1.59153092e+00   1.13713427e-01]
 [ -6.17755573e-02   2.55527507e-01   4.63503884e-01 ...,   2.33510938e-01
   -3.00869266e-01   9.61391442e-01]
 ..., 
 [ -1.84468784e-01  -2.39526779e-01  -3.78767185e-01 ...,   8.99852389e-02
   -6.06981369e-01  -3.16572870e-01]
 [ -2.75743567e-01  -1.84723977e-01  -1.84183196e-01 ...,  -1.18590927e-01
   -1.55922618e-01  -3.43745729e-01]
 [  3.94953258e-02   8.69322145e-02  -4.13718809e-02 ...,   5.44138883e-02
    2.89374935e+00  -6.43530764e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16543659]
 [-0.95105804]
 [-1.19193363]
 [-0.7693532 ]
 [-0.05581424]
 [ 2.60558602]
 [-0.05290771]
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 [ 1.01004657]
 [-0.09384355]
 [ 0.14098221]
 [-0.10957388]
 [-0.99025285]
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 [ 0.87134955]
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 [ 0.13757604]
 [-0.35467466]
 [ 4.468252  ]
 [-0.94860845]
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 [ 0.38153682]
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 [ 4.27880888]
 [-1.89948441]]
[[ -1.82522270e-02  -3.04023302e-01   2.65739835e-01 ...,  -2.31716496e-01
   -3.32729504e-01   2.69511332e-01]
 [  5.85221668e-02   1.46403519e-01   1.89071906e-03 ...,  -2.21982410e-01
    1.59201261e+00   1.13400721e-01]
 [ -6.16668373e-02   2.56188322e-01   4.64152322e-01 ...,   2.33745712e-01
   -3.01859312e-01   9.62920763e-01]
 ..., 
 [ -1.84461294e-01  -2.39486195e-01  -3.78725056e-01 ...,   8.99991805e-02
   -6.07517838e-01  -3.16585878e-01]
 [ -2.75662884e-01  -1.84291974e-01  -1.83718118e-01 ...,  -1.18448948e-01
   -1.57111696e-01  -3.43312066e-01]
 [  3.95454402e-02   8.72362850e-02  -4.10258387e-02 ...,   5.45083814e-02
    2.89366556e+00  -6.37565311e-02]]
Progress: 78.2% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16201662]
 [-0.9478801 ]
 [-1.18920968]
 [-0.76607248]
 [-0.05397298]
 [ 2.60644519]
 [-0.050097  ]
 [-1.08615702]
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 [ 1.01257937]
 [-0.09048551]
 [ 0.14373367]
 [-0.10630515]
 [-0.98823699]
 [-0.29273136]
 [ 0.8740888 ]
 [-0.8325221 ]
 [-0.79061361]
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 [ 0.14018919]
 [-0.35200495]
 [ 4.46844994]
 [-0.94496005]
 [-1.64238787]
 [ 0.38345135]
 [-0.30554508]
 [ 4.28493937]
 [-1.89818286]]
[[ -1.83145128e-02  -3.04402734e-01   2.65957672e-01 ...,  -2.31839375e-01
   -3.32500656e-01   2.69223335e-01]
 [  5.85133745e-02   1.46354055e-01   1.87927953e-03 ...,  -2.21999434e-01
    1.59202604e+00   1.13361213e-01]
 [ -6.16387644e-02   2.56333838e-01   4.64007259e-01 ...,   2.33783292e-01
   -3.01708284e-01   9.62464877e-01]
 ..., 
 [ -1.84598798e-01  -2.40276871e-01  -3.79280877e-01 ...,   8.97493448e-02
   -6.05125181e-01  -3.17565605e-01]
 [ -2.75698187e-01  -1.84482010e-01  -1.83940313e-01 ...,  -1.18509354e-01
   -1.56575227e-01  -3.43623450e-01]
 [  3.94685730e-02   8.67973869e-02  -4.13044569e-02 ...,   5.43675312e-02
    2.89371680e+00  -6.41783959e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16034324]
 [-0.94633729]
 [-1.18707938]
 [-0.76545142]
 [-0.05224681]
 [ 2.60653659]
 [-0.04930141]
 [-1.08483517]
 [-0.52173951]
 [ 1.0143327 ]
 [-0.08981132]
 [ 0.14590628]
 [-0.10507033]
 [-0.9883232 ]
 [-0.29115644]
 [ 0.87778132]
 [-0.83128936]
 [-0.78849155]
 [-0.6130525 ]
 [ 0.14227202]
 [-0.34995545]
 [ 4.46884045]
 [-0.94568307]
 [-1.64029932]
 [ 0.38534334]
 [-0.30430326]
 [ 4.28774778]
 [-1.898831  ]]
[[ -1.84204317e-02  -3.05040282e-01   2.65426617e-01 ...,  -2.32006484e-01
   -3.31109965e-01   2.68728670e-01]
 [  5.85611214e-02   1.46610415e-01   2.28618021e-03 ...,  -2.21905249e-01
    1.59205479e+00   1.14215624e-01]
 [ -6.15782669e-02   2.56593243e-01   4.65413284e-01 ...,   2.33886115e-01
   -3.01589350e-01   9.64261411e-01]
 ..., 
 [ -1.84586848e-01  -2.40223282e-01  -3.79279710e-01 ...,   8.97716915e-02
   -6.05436466e-01  -3.17600851e-01]
 [ -2.75801364e-01  -1.85084505e-01  -1.84506204e-01 ...,  -1.18691492e-01
   -1.55336507e-01  -3.44483904e-01]
 [  3.95685064e-02   8.73409622e-02  -4.05710753e-02 ...,   5.45530970e-02
    2.89361262e+00  -6.32816306e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16325652]
 [-0.94848633]
 [-1.18856913]
 [-0.76760908]
 [-0.05524972]
 [ 2.60764661]
 [-0.05111199]
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 [ 1.0125301 ]
 [-0.09283873]
 [ 0.14328306]
 [-0.10741549]
 [-0.98918448]
 [-0.29402813]
 [ 0.87482961]
 [-0.83399593]
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 [ 0.13950458]
 [-0.35262941]
 [ 4.46850922]
 [-0.94742373]
 [-1.64437326]
 [ 0.38361234]
 [-0.30616786]
 [ 4.28369103]
 [-1.9004662 ]]
[[ -1.83596630e-02  -3.04714954e-01   2.66231195e-01 ...,  -2.31904491e-01
   -3.32137313e-01   2.69090241e-01]
 [  5.85704366e-02   1.46657790e-01   2.35369272e-03 ...,  -2.21888405e-01
    1.59198477e+00   1.14275941e-01]
 [ -6.16866735e-02   2.55946027e-01   4.65292655e-01 ...,   2.33684316e-01
   -3.00417429e-01   9.64725656e-01]
 ..., 
 [ -1.84465444e-01  -2.39545667e-01  -3.78487088e-01 ...,   8.99927852e-02
   -6.06972980e-01  -3.16641900e-01]
 [ -2.75791540e-01  -1.85036502e-01  -1.84394543e-01 ...,  -1.18678178e-01
   -1.55616766e-01  -3.44600672e-01]
 [  3.96254634e-02   8.76892272e-02  -4.00277867e-02 ...,   5.46621404e-02
    2.89361370e+00  -6.25382068e-02]]
Progress: 78.2% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16532124]
 [-0.95040779]
 [-1.19102492]
 [-0.76863113]
 [-0.05648924]
 [ 2.60504729]
 [-0.05319038]
 [-1.08773699]
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 [ 1.01087021]
 [-0.09518142]
 [ 0.14141263]
 [-0.10947438]
 [-0.99239481]
 [-0.29546904]
 [ 0.87167281]
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 [ 0.13728873]
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 [ 4.46649341]
 [-0.94956987]
 [-1.64488682]
 [ 0.38166376]
 [-0.30810047]
 [ 4.28088425]
 [-1.90257156]]
[[ -1.80653156e-02  -3.02974636e-01   2.67805428e-01 ...,  -2.31350539e-01
   -3.36461488e-01   2.72060381e-01]
 [  5.86215788e-02   1.46954761e-01   2.66495615e-03 ...,  -2.21794507e-01
    1.59144258e+00   1.14694667e-01]
 [ -6.14225197e-02   2.57443125e-01   4.66755778e-01 ...,   2.34162220e-01
   -3.04861180e-01   9.67511690e-01]
 ..., 
 [ -1.84466023e-01  -2.39563024e-01  -3.78461229e-01 ...,   8.99912926e-02
   -6.07194462e-01  -3.16636388e-01]
 [ -2.75823544e-01  -1.85211336e-01  -1.84397939e-01 ...,  -1.18733412e-01
   -1.55334570e-01  -3.44730616e-01]
 [  3.94813463e-02   8.68851030e-02  -4.08539290e-02 ...,   5.44026167e-02
    2.89374849e+00  -6.35064969e-02]]
Progress: 78.2% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.15886801]
 [-0.94500316]
 [-1.18511399]
 [-0.76370698]
 [-0.05154346]
 [ 2.6095871 ]
 [-0.04794098]
 [-1.08402627]
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 [ 1.01597937]
 [-0.09017364]
 [ 0.14715273]
 [-0.10333587]
 [-0.98731242]
 [-0.28928342]
 [ 0.87990457]
 [-0.82912697]
 [-0.78719094]
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 [ 0.14260877]
 [-0.3480963 ]
 [ 4.46735341]
 [-0.94547854]
 [-1.64096239]
 [ 0.38726283]
 [-0.30217078]
 [ 4.2903782 ]
 [-1.899193  ]]
[[ -1.82901577e-02  -3.04174518e-01   2.66629379e-01 ...,  -2.31754948e-01
   -3.33174052e-01   2.70204537e-01]
 [  5.86428144e-02   1.47072731e-01   2.76166080e-03 ...,  -2.21757754e-01
    1.59129541e+00   1.14852619e-01]
 [ -6.17588458e-02   2.55568664e-01   4.64565457e-01 ...,   2.33541409e-01
   -3.01918349e-01   9.63988784e-01]
 ..., 
 [ -1.84514606e-01  -2.39884005e-01  -3.79157570e-01 ...,   8.99052107e-02
   -6.05353013e-01  -3.17513699e-01]
 [ -2.75881253e-01  -1.85497387e-01  -1.84756917e-01 ...,  -1.18838313e-01
   -1.54140295e-01  -3.45467100e-01]
 [  3.94161185e-02   8.65268262e-02  -4.12482625e-02 ...,   5.42891591e-02
    2.89395702e+00  -6.41610339e-02]]
Progress: 78.2% ... Training loss: 0.064 ... Validation loss: 0.142[[-0.16293654]
 [-0.94848023]
 [-1.18719449]
 [-0.76822181]
 [-0.05508691]
 [ 2.6079859 ]
 [-0.05183425]
 [-1.08759202]
 [-0.52264082]
 [ 1.01426095]
 [-0.09318732]
 [ 0.14392047]
 [-0.10803878]
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 [-0.29270362]
 [ 0.87595717]
 [-0.83250378]
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 [ 0.13900749]
 [-0.35154018]
 [ 4.46632117]
 [-0.9494317 ]
 [-1.64433706]
 [ 0.38449279]
 [-0.30620235]
 [ 4.28398667]
 [-1.90147365]]
[[ -1.81008255e-02  -3.03067221e-01   2.67551624e-01 ...,  -2.31396616e-01
   -3.35518032e-01   2.72145902e-01]
 [  5.86440041e-02   1.47079953e-01   2.76823965e-03 ...,  -2.21755430e-01
    1.59128528e+00   1.14866995e-01]
 [ -6.17039279e-02   2.55878897e-01   4.65200600e-01 ...,   2.33624058e-01
   -3.03565330e-01   9.65391033e-01]
 ..., 
 [ -1.84425550e-01  -2.39368751e-01  -3.78617306e-01 ...,   9.00705606e-02
   -6.06677324e-01  -3.16652215e-01]
 [ -2.75843772e-01  -1.85265096e-01  -1.84743980e-01 ...,  -1.18766245e-01
   -1.54994738e-01  -3.45143978e-01]
 [  3.94543218e-02   8.67523889e-02  -4.12257642e-02 ...,   5.43520315e-02
    2.89404537e+00  -6.39380002e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16011115]
 [-0.94592809]
 [-1.18466376]
 [-0.76609236]
 [-0.05301123]
 [ 2.61095406]
 [-0.04926121]
 [-1.08583399]
 [-0.520469  ]
 [ 1.01565545]
 [-0.09088026]
 [ 0.14653037]
 [-0.10457317]
 [-0.98787643]
 [-0.29027723]
 [ 0.87871897]
 [-0.82962964]
 [-0.78705965]
 [-0.61152122]
 [ 0.14119019]
 [-0.34955209]
 [ 4.46630258]
 [-0.94685698]
 [-1.64242422]
 [ 0.38694209]
 [-0.30347754]
 [ 4.28884367]
 [-1.90001798]]
[[ -1.83208385e-02  -3.04368833e-01   2.66145509e-01 ...,  -2.31807277e-01
   -3.34085664e-01   2.70164282e-01]
 [  5.86416881e-02   1.47070830e-01   2.76302003e-03 ...,  -2.21758574e-01
    1.59129381e+00   1.14861205e-01]
 [ -6.18140589e-02   2.55145298e-01   4.64301617e-01 ...,   2.33421985e-01
   -3.02311439e-01   9.63841660e-01]
 ..., 
 [ -1.84438888e-01  -2.39430730e-01  -3.78687127e-01 ...,   9.00474157e-02
   -6.05894269e-01  -3.16980288e-01]
 [ -2.75802460e-01  -1.85044096e-01  -1.84694296e-01 ...,  -1.18696121e-01
   -1.55638206e-01  -3.45029400e-01]
 [  3.93681156e-02   8.62330379e-02  -4.14642125e-02 ...,   5.41863867e-02
    2.89412713e+00  -6.47073585e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16397232]
 [-0.95041275]
 [-1.18790731]
 [-0.76958861]
 [-0.05632252]
 [ 2.6066156 ]
 [-0.05327818]
 [-1.08786481]
 [-0.52544874]
 [ 1.01325107]
 [-0.09400546]
 [ 0.14350084]
 [-0.10883372]
 [-0.99187707]
 [-0.29443734]
 [ 0.87456999]
 [-0.83403233]
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 [ 0.13832242]
 [-0.3522411 ]
 [ 4.46588594]
 [-0.94940895]
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 [ 0.38323077]
 [-0.30845996]
 [ 4.28220604]
 [-1.90385972]]
[[ -1.82493040e-02  -3.03928383e-01   2.66817469e-01 ...,  -2.31651501e-01
   -3.35307501e-01   2.71382240e-01]
 [  5.86038101e-02   1.46840888e-01   2.63296182e-03 ...,  -2.21827361e-01
    1.59140047e+00   1.14460739e-01]
 [ -6.13281940e-02   2.57933042e-01   4.67939702e-01 ...,   2.34326910e-01
   -3.08071886e-01   9.68293472e-01]
 ..., 
 [ -1.84349540e-01  -2.38901598e-01  -3.78156369e-01 ...,   9.02149189e-02
   -6.07186069e-01  -3.16215616e-01]
 [ -2.75771851e-01  -1.84855336e-01  -1.84403223e-01 ...,  -1.18631443e-01
   -1.56824239e-01  -3.44461339e-01]
 [  3.94880233e-02   8.69256369e-02  -4.06473966e-02 ...,   5.44123816e-02
    2.89381042e+00  -6.35468889e-02]]
Progress: 78.3% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.15998373]
 [-0.94673399]
 [-1.18415811]
 [-0.76663196]
 [-0.05291634]
 [ 2.60761915]
 [-0.05027597]
 [-1.08508315]
 [-0.52198413]
 [ 1.01629603]
 [-0.09048126]
 [ 0.1471139 ]
 [-0.10506671]
 [-0.99017458]
 [-0.29042508]
 [ 0.87879269]
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 [-0.78563145]
 [-0.61155958]
 [ 0.14198234]
 [-0.34881802]
 [ 4.46653501]
 [-0.94661731]
 [-1.6394977 ]
 [ 0.38585985]
 [-0.30496539]
 [ 4.28838737]
 [-1.90272246]]
[[ -1.83343537e-02  -3.04439229e-01   2.65877956e-01 ...,  -2.31808599e-01
   -3.34352765e-01   2.70650468e-01]
 [  5.86299394e-02   1.46985628e-01   2.52468427e-03 ...,  -2.21779471e-01
    1.59139660e+00   1.14607085e-01]
 [ -6.12987033e-02   2.58073612e-01   4.67652335e-01 ...,   2.34389351e-01
   -3.07752860e-01   9.67600736e-01]
 ..., 
 [ -1.84372232e-01  -2.39012487e-01  -3.78415970e-01 ...,   9.01811160e-02
   -6.07027308e-01  -3.16177353e-01]
 [ -2.75797685e-01  -1.84992702e-01  -1.84497896e-01 ...,  -1.18676305e-01
   -1.56057043e-01  -3.44227910e-01]
 [  3.94208476e-02   8.65307573e-02  -4.09226694e-02 ...,   5.42863934e-02
    2.89370400e+00  -6.38441579e-02]]
Progress: 78.3% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16101754]
 [-0.94775471]
 [-1.18466509]
 [-0.76769441]
 [-0.05362138]
 [ 2.6070989 ]
 [-0.05100568]
 [-1.08604968]
 [-0.52316323]
 [ 1.01609265]
 [-0.09067022]
 [ 0.14626766]
 [-0.10586125]
 [-0.99096175]
 [-0.29117639]
 [ 0.87815074]
 [-0.83098936]
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 [-0.61264073]
 [ 0.14146802]
 [-0.34985397]
 [ 4.46811603]
 [-0.94729831]
 [-1.64019989]
 [ 0.3850845 ]
 [-0.30593456]
 [ 4.28628549]
 [-1.90365248]]
[[ -1.83821864e-02  -3.04764696e-01   2.65441925e-01 ...,  -2.31889938e-01
   -3.33331399e-01   2.70432707e-01]
 [  5.86663946e-02   1.47189118e-01   2.76460940e-03 ...,  -2.21716020e-01
    1.59127772e+00   1.14897714e-01]
 [ -6.12367139e-02   2.58500395e-01   4.68188561e-01 ...,   2.34537645e-01
   -3.07842376e-01   9.68766664e-01]
 ..., 
 [ -1.84350276e-01  -2.38890432e-01  -3.78309548e-01 ...,   9.02218315e-02
   -6.07189939e-01  -3.15984657e-01]
 [ -2.75874653e-01  -1.85443157e-01  -1.85035231e-01 ...,  -1.18814267e-01
   -1.55547111e-01  -3.44875876e-01]
 [  3.95370881e-02   8.71901224e-02  -4.02947746e-02 ...,   5.45021173e-02
    2.89357125e+00  -6.29831568e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16076995]
 [-0.94805755]
 [-1.18409987]
 [-0.7677205 ]
 [-0.05420242]
 [ 2.60692755]
 [-0.05098595]
 [-1.08595047]
 [-0.52354438]
 [ 1.01591185]
 [-0.09112374]
 [ 0.14599522]
 [-0.10628976]
 [-0.99133712]
 [-0.29137698]
 [ 0.87718313]
 [-0.8305113 ]
 [-0.78536898]
 [-0.61297377]
 [ 0.14108403]
 [-0.35035094]
 [ 4.46757462]
 [-0.94668485]
 [-1.6390329 ]
 [ 0.38500072]
 [-0.30630255]
 [ 4.28703046]
 [-1.90348848]]
[[-0.01834654 -0.3045654   0.26584587 ..., -0.23182853 -0.33490678
   0.27105853]
 [ 0.05868037  0.14727526  0.00291292 ..., -0.22168491  1.59102368
   0.11515011]
 [-0.06119174  0.25875711  0.4683916  ...,  0.23462729 -0.31026994
   0.96930852]
 ..., 
 [-0.18434175 -0.238819   -0.37821634 ...,  0.09024047 -0.60749332
  -0.31580062]
 [-0.27585949 -0.18537385 -0.18487645 ..., -0.11878528 -0.15583897
  -0.34468839]
 [ 0.03943768  0.08660287 -0.04077336 ...,  0.05431757  2.89365761
  -0.06399558]]
Progress: 78.3% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16244407]
 [-0.94954911]
 [-1.18449047]
 [-0.76948137]
 [-0.05519055]
 [ 2.60655866]
 [-0.05204686]
 [-1.08777096]
 [-0.52408586]
 [ 1.01558652]
 [-0.09238796]
 [ 0.14496826]
 [-0.10765044]
 [-0.99125584]
 [-0.29257683]
 [ 0.87638946]
 [-0.83227019]
 [-0.78631276]
 [-0.61353636]
 [ 0.14029899]
 [-0.35119726]
 [ 4.46803501]
 [-0.94842229]
 [-1.64149384]
 [ 0.38454352]
 [-0.30756169]
 [ 4.28389045]
 [-1.9032963 ]]
[[ -1.83460932e-02  -3.04509974e-01   2.65685998e-01 ...,  -2.31820220e-01
   -3.34150032e-01   2.70199434e-01]
 [  5.86583790e-02   1.47149012e-01   2.76214410e-03 ...,  -2.21737193e-01
    1.59174785e+00   1.14751939e-01]
 [ -6.12902043e-02   2.58250516e-01   4.67922714e-01 ...,   2.34490876e-01
   -3.08040552e-01   9.69078261e-01]
 ..., 
 [ -1.84364451e-01  -2.38939399e-01  -3.78299402e-01 ...,   9.02024737e-02
   -6.07007289e-01  -3.15879764e-01]
 [ -2.75888292e-01  -1.85532432e-01  -1.84973457e-01 ...,  -1.18834634e-01
   -1.55025698e-01  -3.45131702e-01]
 [  3.95520912e-02   8.72611150e-02  -4.03215302e-02 ...,   5.45226289e-02
    2.89349778e+00  -6.29811215e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16281089]
 [-0.94921712]
 [-1.18579618]
 [-0.76865031]
 [-0.05537602]
 [ 2.60798934]
 [-0.05104385]
 [-1.08863038]
 [-0.52425642]
 [ 1.01463523]
 [-0.09248287]
 [ 0.14485851]
 [-0.10693324]
 [-0.98943875]
 [-0.29303811]
 [ 0.87525874]
 [-0.83281202]
 [-0.78735862]
 [-0.61522302]
 [ 0.14038032]
 [-0.35195357]
 [ 4.4680644 ]
 [-0.94696275]
 [-1.64362823]
 [ 0.38466503]
 [-0.30735863]
 [ 4.28319624]
 [-1.90216761]]
[[ -1.83645785e-02  -3.04592112e-01   2.65660569e-01 ...,  -2.31848835e-01
   -3.32863143e-01   2.69921761e-01]
 [  5.86518837e-02   1.47117543e-01   2.74474376e-03 ...,  -2.21748380e-01
    1.59179998e+00   1.14741033e-01]
 [ -6.14487755e-02   2.57289791e-01   4.66590629e-01 ...,   2.34185161e-01
   -3.06965916e-01   9.67178983e-01]
 ..., 
 [ -1.84395494e-01  -2.39142605e-01  -3.78501455e-01 ...,   9.01433293e-02
   -6.06034821e-01  -3.16307448e-01]
 [ -2.75883737e-01  -1.85482024e-01  -1.84920572e-01 ...,  -1.18823266e-01
   -1.55038522e-01  -3.44981853e-01]
 [  3.95937667e-02   8.74946220e-02  -4.01502279e-02 ...,   5.46006640e-02
    2.89334955e+00  -6.30095171e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16388809]
 [-0.9501155 ]
 [-1.18762466]
 [-0.7691155 ]
 [-0.05627729]
 [ 2.60782761]
 [-0.05096875]
 [-1.08938603]
 [-0.52567855]
 [ 1.01343054]
 [-0.09296159]
 [ 0.14389375]
 [-0.10712112]
 [-0.98909097]
 [-0.29439661]
 [ 0.87336038]
 [-0.83425162]
 [-0.78897881]
 [-0.61731942]
 [ 0.13941256]
 [-0.3530323 ]
 [ 4.46945136]
 [-0.94692964]
 [-1.6451025 ]
 [ 0.38400823]
 [-0.30817153]
 [ 4.28200607]
 [-1.90260137]]
[[ -1.84039720e-02  -3.04854609e-01   2.65250545e-01 ...,  -2.31920389e-01
   -3.32848124e-01   2.69007033e-01]
 [  5.85392666e-02   1.46460185e-01   2.02818255e-03 ...,  -2.21953070e-01
    1.59251499e+00   1.13694769e-01]
 [ -6.13612726e-02   2.57761617e-01   4.67354390e-01 ...,   2.34363908e-01
   -3.06664837e-01   9.67626222e-01]
 ..., 
 [ -1.84423401e-01  -2.39301595e-01  -3.78768695e-01 ...,   9.00968730e-02
   -6.06005657e-01  -3.16872291e-01]
 [ -2.75855874e-01  -1.85321392e-01  -1.84811101e-01 ...,  -1.18769341e-01
   -1.55562579e-01  -3.44768807e-01]
 [  3.95946915e-02   8.74945683e-02  -4.01447518e-02 ...,   5.46062108e-02
    2.89351310e+00  -6.27762631e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15762559]
 [-0.94470779]
 [-1.18316622]
 [-0.76384999]
 [-0.0520349 ]
 [ 2.6124415 ]
 [-0.04512181]
 [-1.08530864]
 [-0.52038886]
 [ 1.01665769]
 [-0.08836167]
 [ 0.1492995 ]
 [-0.10130493]
 [-0.98475064]
 [-0.2888179 ]
 [ 0.88028677]
 [-0.82860007]
 [-0.78461127]
 [-0.61232755]
 [ 0.14438264]
 [-0.34790084]
 [ 4.47067002]
 [-0.94286963]
 [-1.64071005]
 [ 0.38911242]
 [-0.30297953]
 [ 4.29248307]
 [-1.89885309]]
[[ -1.86602486e-02  -3.06359747e-01   2.63815478e-01 ...,  -2.32386116e-01
   -3.31493898e-01   2.66226802e-01]
 [  5.85469562e-02   1.46493607e-01   2.08435986e-03 ...,  -2.21940255e-01
    1.59246240e+00   1.13736033e-01]
 [ -6.15833977e-02   2.56468101e-01   4.65778916e-01 ...,   2.33968479e-01
   -3.05495942e-01   9.64953864e-01]
 ..., 
 [ -1.84498315e-01  -2.39742841e-01  -3.79098654e-01 ...,   8.99655848e-02
   -6.04798964e-01  -3.17540961e-01]
 [ -2.75898359e-01  -1.85583567e-01  -1.85234941e-01 ...,  -1.18852348e-01
   -1.54645475e-01  -3.45251226e-01]
 [  3.95840640e-02   8.74396669e-02  -4.01547508e-02 ...,   5.45851355e-02
    2.89357083e+00  -6.31234020e-02]]
Progress: 78.3% ... Training loss: 0.067 ... Validation loss: 0.148[[-0.16316224]
 [-0.94898547]
 [-1.18699873]
 [-0.76824078]
 [-0.05727344]
 [ 2.60998474]
 [-0.04990255]
 [-1.08933979]
 [-0.52545909]
 [ 1.01354369]
 [-0.09332045]
 [ 0.14496713]
 [-0.10621399]
 [-0.9895397 ]
 [-0.2937012 ]
 [ 0.8752967 ]
 [-0.83362586]
 [-0.78899693]
 [-0.61624357]
 [ 0.13992268]
 [-0.35210796]
 [ 4.46982445]
 [-0.94817622]
 [-1.64492395]
 [ 0.38519643]
 [-0.30742596]
 [ 4.28465895]
 [-1.90198565]]
[[ -1.85048560e-02  -3.05456006e-01   2.65050182e-01 ...,  -2.32110877e-01
   -3.35095678e-01   2.67601806e-01]
 [  5.85824545e-02   1.46722061e-01   2.36341653e-03 ...,  -2.21877779e-01
    1.59230896e+00   1.14163174e-01]
 [ -6.14673529e-02   2.57241555e-01   4.66992834e-01 ...,   2.34213679e-01
   -3.08590516e-01   9.67721215e-01]
 ..., 
 [ -1.84469315e-01  -2.39593225e-01  -3.78926784e-01 ...,   9.00173744e-02
   -6.05351083e-01  -3.17332026e-01]
 [ -2.75831051e-01  -1.85225270e-01  -1.84954519e-01 ...,  -1.18728989e-01
   -1.57049099e-01  -3.44401859e-01]
 [  3.96658783e-02   8.79258620e-02  -3.95508051e-02 ...,   5.47370935e-02
    2.89329791e+00  -6.24372516e-02]]
Progress: 78.3% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16259687]
 [-0.94823926]
 [-1.18753561]
 [-0.76685105]
 [-0.05644096]
 [ 2.61010087]
 [-0.04956621]
 [-1.08812272]
 [-0.52531607]
 [ 1.01338264]
 [-0.09331662]
 [ 0.14489381]
 [-0.10585072]
 [-0.99029429]
 [-0.29282649]
 [ 0.87530995]
 [-0.83304991]
 [-0.78982326]
 [-0.61638139]
 [ 0.14012593]
 [-0.35217332]
 [ 4.46823177]
 [-0.94751513]
 [-1.64455656]
 [ 0.38496247]
 [-0.30654198]
 [ 4.28558531]
 [-1.90275198]]
[[ -1.82839334e-02  -3.04275149e-01   2.66429631e-01 ...,  -2.31719277e-01
   -3.37734438e-01   2.69288582e-01]
 [  5.86220312e-02   1.46944798e-01   2.60216132e-03 ...,  -2.21808007e-01
    1.59219014e+00   1.14419418e-01]
 [ -6.14035817e-02   2.57658635e-01   4.67436525e-01 ...,   2.34341653e-01
   -3.11207171e-01   9.68669535e-01]
 ..., 
 [ -1.84416974e-01  -2.39307401e-01  -3.78503188e-01 ...,   9.01138912e-02
   -6.06121400e-01  -3.16579482e-01]
 [ -2.75846223e-01  -1.85311537e-01  -1.85003338e-01 ...,  -1.18754341e-01
   -1.57033544e-01  -3.44621549e-01]
 [  3.95069066e-02   8.70033148e-02  -4.05783293e-02 ...,   5.44327498e-02
    2.89352481e+00  -6.35783841e-02]]
Progress: 78.3% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.1650935 ]
 [-0.94979873]
 [-1.18830303]
 [-0.76931066]
 [-0.05852729]
 [ 2.609649  ]
 [-0.05139387]
 [-1.09108741]
 [-0.52660055]
 [ 1.01159115]
 [-0.09603348]
 [ 0.14278541]
 [-0.10733613]
 [-0.99164225]
 [-0.29437704]
 [ 0.87280707]
 [-0.83491579]
 [-0.79196795]
 [-0.61807927]
 [ 0.13827977]
 [-0.35444498]
 [ 4.46848149]
 [-0.95030671]
 [-1.64806585]
 [ 0.38344922]
 [-0.30750996]
 [ 4.28213673]
 [-1.90328268]]
[[ -1.82774928e-02  -3.04234511e-01   2.66476811e-01 ...,  -2.31709389e-01
   -3.37200216e-01   2.68967741e-01]
 [  5.86130166e-02   1.46892515e-01   2.53382146e-03 ...,  -2.21829203e-01
    1.59213142e+00   1.14448636e-01]
 [ -6.15240485e-02   2.56979488e-01   4.66605200e-01 ...,   2.34116059e-01
   -3.10527717e-01   9.68350824e-01]
 ..., 
 [ -1.84383641e-01  -2.39094336e-01  -3.78509143e-01 ...,   9.01794835e-02
   -6.07044787e-01  -3.16613867e-01]
 [ -2.75775201e-01  -1.84913363e-01  -1.84662992e-01 ...,  -1.18629207e-01
   -1.58385295e-01  -3.43984706e-01]
 [  3.94514688e-02   8.66810161e-02  -4.08807933e-02 ...,   5.43333129e-02
    2.89362926e+00  -6.39837754e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16227392]
 [-0.94621751]
 [-1.18732894]
 [-0.76671282]
 [-0.05639976]
 [ 2.61134596]
 [-0.04863246]
 [-1.08856389]
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 [ 1.01302481]
 [-0.09343397]
 [ 0.14548103]
 [-0.10466954]
 [-0.98991009]
 [-0.29128505]
 [ 0.87449169]
 [-0.83203128]
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 [ 0.14094586]
 [-0.35185137]
 [ 4.46803958]
 [-0.94739367]
 [-1.64544511]
 [ 0.38528557]
 [-0.30392059]
 [ 4.2878156 ]
 [-1.90244224]]
[[ -1.82101478e-02  -3.03811235e-01   2.66772558e-01 ...,  -2.31591560e-01
   -3.38616994e-01   2.70302973e-01]
 [  5.85526245e-02   1.46560529e-01   2.12955054e-03 ...,  -2.21940997e-01
    1.59232642e+00   1.13794461e-01]
 [ -6.15779078e-02   2.56665875e-01   4.65952406e-01 ...,   2.33989817e-01
   -3.12128316e-01   9.67113254e-01]
 ..., 
 [ -1.84482169e-01  -2.39640822e-01  -3.79041498e-01 ...,   9.00001385e-02
   -6.05746110e-01  -3.17499265e-01]
 [ -2.75648163e-01  -1.84207944e-01  -1.84396341e-01 ...,  -1.18409041e-01
   -1.58869826e-01  -3.42487770e-01]
 [  3.93353227e-02   8.60633295e-02  -4.16422463e-02 ...,   5.41189203e-02
    2.89373544e+00  -6.47482461e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16434173]
 [-0.94808804]
 [-1.18838429]
 [-0.76800483]
 [-0.05716845]
 [ 2.60918684]
 [-0.05067475]
 [-1.08808418]
 [-0.52588188]
 [ 1.01264974]
 [-0.09436339]
 [ 0.14437541]
 [-0.10671137]
 [-0.99305821]
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 [ 0.87331706]
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 [ 0.139285  ]
 [-0.35333278]
 [ 4.46682723]
 [-0.94999731]
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 [ 0.38328654]
 [-0.30563961]
 [ 4.28466847]
 [-1.90512639]]
[[ -1.80279566e-02  -3.02765830e-01   2.67931069e-01 ...,  -2.31263456e-01
   -3.40145244e-01   2.72669533e-01]
 [  5.85850268e-02   1.46735570e-01   2.29029398e-03 ...,  -2.21884814e-01
    1.59217033e+00   1.13992963e-01]
 [ -6.12981750e-02   2.58262494e-01   4.67449873e-01 ...,   2.34489246e-01
   -3.14803374e-01   9.69212345e-01]
 ..., 
 [ -1.84435214e-01  -2.39377503e-01  -3.78703091e-01 ...,   9.00820537e-02
   -6.06353480e-01  -3.16995915e-01]
 [ -2.75655952e-01  -1.84249300e-01  -1.84274045e-01 ...,  -1.18421000e-01
   -1.58693907e-01  -3.42049463e-01]
 [  3.93896604e-02   8.63863092e-02  -4.17308116e-02 ...,   5.42060066e-02
    2.89365101e+00  -6.43374154e-02]]
Progress: 78.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16283539]
 [-0.94746569]
 [-1.1862952 ]
 [-0.76820644]
 [-0.05677628]
 [ 2.61088918]
 [-0.04979434]
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 [ 1.01443511]
 [-0.09347433]
 [ 0.14530978]
 [-0.10529938]
 [-0.99116935]
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 [ 0.87447205]
 [-0.83195738]
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 [-0.61482016]
 [ 0.14041905]
 [-0.35204952]
 [ 4.46754545]
 [-0.94865574]
 [-1.64466878]
 [ 0.38405119]
 [-0.30460895]
 [ 4.2863605 ]
 [-1.90368614]]
[[ -1.82014881e-02  -3.03675011e-01   2.66812958e-01 ...,  -2.31586484e-01
   -3.37328402e-01   2.71603753e-01]
 [  5.86190372e-02   1.46931869e-01   2.44905018e-03 ...,  -2.21822676e-01
    1.59198428e+00   1.14202795e-01]
 [ -6.14723575e-02   2.57088943e-01   4.66449471e-01 ...,   2.34112872e-01
   -3.12655416e-01   9.66958880e-01]
 ..., 
 [ -1.84547872e-01  -2.40027602e-01  -3.79453272e-01 ...,   8.98723649e-02
   -6.04016584e-01  -3.18160586e-01]
 [ -2.75672598e-01  -1.84318570e-01  -1.84309250e-01 ...,  -1.18447716e-01
   -1.58139269e-01  -3.42123424e-01]
 [  3.93488893e-02   8.61691479e-02  -4.21070570e-02 ...,   5.41279437e-02
    2.89389292e+00  -6.49328081e-02]]
Progress: 78.4% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16329003]
 [-0.94826619]
 [-1.18694016]
 [-0.76859075]
 [-0.05639739]
 [ 2.60984642]
 [-0.05036336]
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 [ 1.01453843]
 [-0.09405767]
 [ 0.14482135]
 [-0.10569323]
 [-0.992736  ]
 [-0.29158603]
 [ 0.87445062]
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 [ 0.14042575]
 [-0.35186307]
 [ 4.46732242]
 [-0.94975072]
 [-1.64378792]
 [ 0.38326792]
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 [ 4.28590904]
 [-1.90499436]]
[[ -1.81856480e-02  -3.03597001e-01   2.67149481e-01 ...,  -2.31551063e-01
   -3.38201940e-01   2.72196582e-01]
 [  5.85912164e-02   1.46777571e-01   2.25388316e-03 ...,  -2.21876735e-01
    1.59208495e+00   1.13859366e-01]
 [ -6.12616200e-02   2.58202318e-01   4.67769750e-01 ...,   2.34505112e-01
   -3.14410915e-01   9.68703655e-01]
 ..., 
 [ -1.84466591e-01  -2.39575150e-01  -3.78919029e-01 ...,   9.00193373e-02
   -6.05049690e-01  -3.17332157e-01]
 [ -2.75554484e-01  -1.83652313e-01  -1.83734331e-01 ...,  -1.18245692e-01
   -1.60270831e-01  -3.41123846e-01]
 [  3.92730998e-02   8.57397840e-02  -4.24660929e-02 ...,   5.39962137e-02
    2.89431211e+00  -6.55033326e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16043773]
 [-0.94616954]
 [-1.18580314]
 [-0.76562123]
 [-0.05408187]
 [ 2.61170846]
 [-0.04752216]
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 [ 1.01518187]
 [-0.0920456 ]
 [ 0.14721982]
 [-0.10242416]
 [-0.98978599]
 [-0.28936835]
 [ 0.87690114]
 [-0.83061438]
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 [ 0.14267187]
 [-0.34926155]
 [ 4.46862954]
 [-0.94648161]
 [-1.64146541]
 [ 0.38532689]
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 [ 4.29012887]
 [-1.90347293]]
[[ -1.83693903e-02  -3.04577611e-01   2.66169483e-01 ...,  -2.31859687e-01
   -3.34873358e-01   2.71069815e-01]
 [  5.85312295e-02   1.46454893e-01   2.07506761e-03 ...,  -2.21977637e-01
    1.59247539e+00   1.13534688e-01]
 [ -6.12997298e-02   2.57986502e-01   4.67636509e-01 ...,   2.34422981e-01
   -3.11496132e-01   9.67935892e-01]
 ..., 
 [ -1.84505873e-01  -2.39799856e-01  -3.79125918e-01 ...,   8.99456586e-02
   -6.04194419e-01  -3.17783059e-01]
 [ -2.75700055e-01  -1.84499807e-01  -1.84490671e-01 ...,  -1.18496964e-01
   -1.58684263e-01  -3.42269963e-01]
 [  3.92470465e-02   8.55795734e-02  -4.26714331e-02 ...,   5.39372977e-02
    2.89430231e+00  -6.56750144e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.1625023 ]
 [-0.94919278]
 [-1.18793691]
 [-0.76775007]
 [-0.05658047]
 [ 2.61125882]
 [-0.0496465 ]
 [-1.08749407]
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 [ 1.0136859 ]
 [-0.09422194]
 [ 0.14531574]
 [-0.1043773 ]
 [-0.99042351]
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 [ 0.87473543]
 [-0.83321433]
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 [ 0.14025345]
 [-0.35064088]
 [ 4.46709842]
 [-0.94741328]
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 [ 0.38414761]
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 [ 4.28559156]
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[[ -1.82050469e-02  -3.03589020e-01   2.66916302e-01 ...,  -2.31541033e-01
   -3.34211195e-01   2.71911935e-01]
 [  5.85375582e-02   1.46490189e-01   2.08654441e-03 ...,  -2.21965693e-01
    1.59250383e+00   1.13521299e-01]
 [ -6.13181257e-02   2.57774261e-01   4.67566671e-01 ...,   2.34366228e-01
   -3.10738398e-01   9.67769863e-01]
 ..., 
 [ -1.84489928e-01  -2.39691041e-01  -3.79081716e-01 ...,   8.99773994e-02
   -6.04062753e-01  -3.17490007e-01]
 [ -2.75721647e-01  -1.84619238e-01  -1.84679204e-01 ...,  -1.18528993e-01
   -1.57055428e-01  -3.42785811e-01]
 [  3.92388160e-02   8.55371875e-02  -4.27308171e-02 ...,   5.39267716e-02
    2.89444261e+00  -6.57387549e-02]]
Progress: 78.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16219593]
 [-0.94872524]
 [-1.1870059 ]
 [-0.76822102]
 [-0.05542905]
 [ 2.61212766]
 [-0.04956464]
 [-1.08817848]
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 [ 1.01510594]
 [-0.09326821]
 [ 0.14603633]
 [-0.10397158]
 [-0.99026351]
 [-0.29136623]
 [ 0.87628434]
 [-0.83250902]
 [-0.79025604]
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 [ 0.14096082]
 [-0.35008593]
 [ 4.46738673]
 [-0.94815676]
 [-1.64443835]
 [ 0.38486602]
 [-0.30459513]
 [ 4.28502087]
 [-1.90322815]]
[[ -1.82426457e-02  -3.03851016e-01   2.66796632e-01 ...,  -2.31640754e-01
   -3.32256343e-01   2.71909685e-01]
 [  5.85493080e-02   1.46551170e-01   2.13910443e-03 ...,  -2.21958885e-01
    1.59244564e+00   1.13883017e-01]
 [ -6.14857513e-02   2.56832536e-01   4.67152227e-01 ...,   2.34028434e-01
   -3.06005686e-01   9.66863332e-01]
 ..., 
 [ -1.84513556e-01  -2.39842667e-01  -3.79145052e-01 ...,   8.99303626e-02
   -6.02913002e-01  -3.17753678e-01]
 [ -2.75696107e-01  -1.84510134e-01  -1.84652156e-01 ...,  -1.18503757e-01
   -1.55908785e-01  -3.42925842e-01]
 [  3.92763747e-02   8.57724438e-02  -4.26231494e-02 ...,   5.39993947e-02
    2.89441882e+00  -6.54872240e-02]]
Progress: 78.4% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16374754]
 [-0.95071042]
 [-1.18982321]
 [-0.76914342]
 [-0.05603866]
 [ 2.61084379]
 [-0.05118241]
 [-1.08892041]
 [-0.52619276]
 [ 1.01355203]
 [-0.09392295]
 [ 0.14442286]
 [-0.1059165 ]
 [-0.99141672]
 [-0.29389207]
 [ 0.87340488]
 [-0.83471491]
 [-0.79209447]
 [-0.61713003]
 [ 0.13959523]
 [-0.35209593]
 [ 4.46791949]
 [-0.94778353]
 [-1.64523058]
 [ 0.3831454 ]
 [-0.30684075]
 [ 4.28199881]
 [-1.90419023]]
[[ -1.81940530e-02  -3.03553585e-01   2.67026668e-01 ...,  -2.31534439e-01
   -3.31745254e-01   2.72733317e-01]
 [  5.85336352e-02   1.46458596e-01   2.10325250e-03 ...,  -2.21988518e-01
    1.59246945e+00   1.13800975e-01]
 [ -6.13293004e-02   2.57780288e-01   4.67521625e-01 ...,   2.34326073e-01
   -3.06796930e-01   9.67419938e-01]
 ..., 
 [ -1.84491793e-01  -2.39719229e-01  -3.79046958e-01 ...,   8.99783304e-02
   -6.02908009e-01  -3.17565421e-01]
 [ -2.75717265e-01  -1.84657024e-01  -1.84894440e-01 ...,  -1.18538178e-01
   -1.56005489e-01  -3.43030807e-01]
 [  3.93487722e-02   8.61753904e-02  -4.19456757e-02 ...,   5.41193920e-02
    2.89423634e+00  -6.45087186e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16036526]
 [-0.948017  ]
 [-1.18833514]
 [-0.76514612]
 [-0.05257456]
 [ 2.61115961]
 [-0.04850564]
 [-1.08484055]
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 [ 1.01509856]
 [-0.09044212]
 [ 0.14749391]
 [-0.10280287]
 [-0.99099573]
 [-0.29122775]
 [ 0.8771906 ]
 [-0.831578  ]
 [-0.78991539]
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 [ 0.14239022]
 [-0.34929065]
 [ 4.46834883]
 [-0.94482314]
 [-1.63999334]
 [ 0.38489382]
 [-0.30467404]
 [ 4.28816722]
 [-1.90354213]]
[[ -1.82945891e-02  -3.04087448e-01   2.66638657e-01 ...,  -2.31727391e-01
   -3.31260839e-01   2.72547646e-01]
 [  5.85471048e-02   1.46541177e-01   2.20761597e-03 ...,  -2.21971405e-01
    1.59249831e+00   1.14164959e-01]
 [ -6.10823328e-02   2.59191852e-01   4.68897404e-01 ...,   2.34748614e-01
   -3.09430808e-01   9.67944860e-01]
 ..., 
 [ -1.84552443e-01  -2.40057603e-01  -3.79324630e-01 ...,   8.98707210e-02
   -6.01976936e-01  -3.18201194e-01]
 [ -2.75806702e-01  -1.85137044e-01  -1.85146117e-01 ...,  -1.18697004e-01
   -1.54825884e-01  -3.43579626e-01]
 [  3.91869704e-02   8.52615913e-02  -4.27415323e-02 ...,   5.38162073e-02
    2.89438192e+00  -6.55545389e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16584672]
 [-0.95262065]
 [-1.19309148]
 [-0.76935396]
 [-0.05779413]
 [ 2.60751842]
 [-0.05298798]
 [-1.08876748]
 [-0.52992011]
 [ 1.01169187]
 [-0.09515758]
 [ 0.14236608]
 [-0.10783781]
 [-0.99386822]
 [-0.29687753]
 [ 0.86963909]
 [-0.83691012]
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 [ 0.13793835]
 [-0.35444232]
 [ 4.46695433]
 [-0.94757583]
 [-1.6440715 ]
 [ 0.38061976]
 [-0.30982559]
 [ 4.27996164]
 [-1.90505553]]
[[ -1.80622859e-02  -3.02793683e-01   2.68195650e-01 ...,  -2.31287479e-01
   -3.35956163e-01   2.74627115e-01]
 [  5.85618238e-02   1.46634736e-01   2.29138343e-03 ...,  -2.21942058e-01
    1.59191659e+00   1.14357698e-01]
 [ -6.09400252e-02   2.60017029e-01   4.69757897e-01 ...,   2.35020517e-01
   -3.12741759e-01   9.69254919e-01]
 ..., 
 [ -1.84520569e-01  -2.39868983e-01  -3.79130539e-01 ...,   8.99342839e-02
   -6.02408851e-01  -3.18189455e-01]
 [ -2.75792163e-01  -1.85059100e-01  -1.84988717e-01 ...,  -1.18670814e-01
   -1.55385627e-01  -3.43351661e-01]
 [  3.93135705e-02   8.59730403e-02  -4.22397120e-02 ...,   5.40421436e-02
    2.89417816e+00  -6.46513503e-02]]
Progress: 78.4% ... Training loss: 0.065 ... Validation loss: 0.142[[-0.16262839]
 [-0.95017759]
 [-1.19131899]
 [-0.76587164]
 [-0.05539934]
 [ 2.60783444]
 [-0.05083478]
 [-1.08623998]
 [-0.5272582 ]
 [ 1.01313091]
 [-0.09250014]
 [ 0.14467154]
 [-0.10544659]
 [-0.99278829]
 [-0.29427503]
 [ 0.87203133]
 [-0.83355613]
 [-0.79191198]
 [-0.61801323]
 [ 0.14038037]
 [-0.35193036]
 [ 4.4669314 ]
 [-0.94572815]
 [-1.64129054]
 [ 0.38195466]
 [-0.30728054]
 [ 4.28483173]
 [-1.90424982]]
[[ -1.80776001e-02  -3.02913391e-01   2.68076775e-01 ...,  -2.31333189e-01
   -3.35685532e-01   2.74895094e-01]
 [  5.85755256e-02   1.46713010e-01   2.31740872e-03 ...,  -2.21917264e-01
    1.59183641e+00   1.14409020e-01]
 [ -6.09251251e-02   2.60107933e-01   4.69603621e-01 ...,   2.35035531e-01
   -3.10130281e-01   9.68773874e-01]
 ..., 
 [ -1.84557839e-01  -2.40072735e-01  -3.79691532e-01 ...,   8.98603775e-02
   -6.01222768e-01  -3.18994566e-01]
 [ -2.75736362e-01  -1.84771233e-01  -1.84634591e-01 ...,  -1.18592572e-01
   -1.55255652e-01  -3.43087005e-01]
 [  3.92540629e-02   8.56197219e-02  -4.24629073e-02 ...,   5.39323885e-02
    2.89420315e+00  -6.51397140e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16202725]
 [-0.94924226]
 [-1.19127038]
 [-0.76554519]
 [-0.05480132]
 [ 2.60801233]
 [-0.05036733]
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 [ 1.01306575]
 [-0.09195094]
 [ 0.1453741 ]
 [-0.10448168]
 [-0.99335497]
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 [ 0.8733112 ]
 [-0.83321509]
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 [ 0.14135908]
 [-0.3512946 ]
 [ 4.46723174]
 [-0.94672474]
 [-1.64105449]
 [ 0.38294828]
 [-0.30645616]
 [ 4.28719962]
 [-1.90386178]]
[[ -1.81056560e-02  -3.03117865e-01   2.68182970e-01 ...,  -2.31399807e-01
   -3.37842684e-01   2.74574829e-01]
 [  5.86409539e-02   1.47108312e-01   2.78346345e-03 ...,  -2.21809151e-01
    1.59151413e+00   1.15187140e-01]
 [ -6.09805720e-02   2.59699879e-01   4.69629134e-01 ...,   2.34901465e-01
   -3.11150525e-01   9.69001936e-01]
 ..., 
 [ -1.84580763e-01  -2.40201123e-01  -3.79874769e-01 ...,   8.98153036e-02
   -6.00407505e-01  -3.19485159e-01]
 [ -2.75737132e-01  -1.84830872e-01  -1.84517773e-01 ...,  -1.18608930e-01
   -1.55692236e-01  -3.42996889e-01]
 [  3.92388769e-02   8.55182853e-02  -4.24769233e-02 ...,   5.39025389e-02
    2.89445107e+00  -6.51694853e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.15905722]
 [-0.94656394]
 [-1.19005216]
 [-0.76358052]
 [-0.05351251]
 [ 2.61143046]
 [-0.04737807]
 [-1.08661951]
 [-0.52332268]
 [ 1.01483253]
 [-0.09034937]
 [ 0.14736963]
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 [ 0.87575478]
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 [ 0.14422226]
 [-0.34788625]
 [ 4.467912  ]
 [-0.94323293]
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 [ 0.38623465]
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 [ 4.29226016]
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[[-0.0181788  -0.30348493  0.26780854 ..., -0.23148862 -0.33738569
   0.27357173]
 [ 0.05866174  0.14721857  0.00292743 ..., -0.2217634   1.59155763
   0.1152114 ]
 [-0.06132185  0.25770846  0.46738767 ...,  0.23428562 -0.30763354
   0.96608726]
 ..., 
 [-0.18458251 -0.24019444 -0.38002952 ...,  0.08981565 -0.60044221
  -0.31964876]
 [-0.27580593 -0.18524646 -0.1850418  ..., -0.11872976 -0.15466936
  -0.34378506]
 [ 0.03918154  0.08520611 -0.0423256  ...,  0.0538183   2.89486647
  -0.06607805]]
Progress: 78.4% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.1617252 ]
 [-0.94873165]
 [-1.19293101]
 [-0.76554667]
 [-0.0554089 ]
 [ 2.6103785 ]
 [-0.04934461]
 [-1.08847503]
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 [ 1.01270322]
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 [ 0.14483433]
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 [ 0.87233436]
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 [ 0.14200887]
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 [ 4.46844485]
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 [ 0.38415393]
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 [ 4.28825447]
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[[-0.01813587 -0.30323635  0.26828134 ..., -0.23140083 -0.33794695
   0.27424982]
 [ 0.05866761  0.14722964  0.00301368 ..., -0.22175469  1.59142348
   0.11520279]
 [-0.06126752  0.25807534  0.46800283 ...,  0.23441144 -0.30856188
   0.9674075 ]
 ..., 
 [-0.18459197 -0.24026679 -0.37998005 ...,  0.08979411 -0.60053587
  -0.3197594 ]
 [-0.27578265 -0.18513962 -0.18487028 ..., -0.11868624 -0.15480984
  -0.34370994]
 [ 0.03923131  0.08549678 -0.04196384 ...,  0.05390874  2.89478396
  -0.06539499]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16172619]
 [-0.94751429]
 [-1.19114906]
 [-0.76636413]
 [-0.05497757]
 [ 2.60972393]
 [-0.049411  ]
 [-1.08935402]
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 [ 1.01456061]
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 [ 0.14526658]
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 [ 0.14211197]
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 [ 4.46902891]
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 [ 0.38464641]
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 [ 4.28820116]
 [-1.90195806]]
[[ -1.80240214e-02  -3.02623526e-01   2.68631462e-01 ...,  -2.31183350e-01
   -3.38574419e-01   2.74972051e-01]
 [  5.86405878e-02   1.47074178e-01   2.82655281e-03 ...,  -2.21805253e-01
    1.59195775e+00   1.14888317e-01]
 [ -6.14935199e-02   2.56877660e-01   4.66935620e-01 ...,   2.34002455e-01
   -3.06207992e-01   9.65863095e-01]
 ..., 
 [ -1.84619016e-01  -2.40402023e-01  -3.80239898e-01 ...,   8.97462731e-02
   -5.99558364e-01  -3.20116261e-01]
 [ -2.75838557e-01  -1.85468401e-01  -1.85408229e-01 ...,  -1.18793600e-01
   -1.54435460e-01  -3.44721331e-01]
 [  3.92546919e-02   8.56201211e-02  -4.18977137e-02 ...,   5.39494136e-02
    2.89480812e+00  -6.53286963e-02]]
Progress: 78.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15981229]
 [-0.94576098]
 [-1.18918268]
 [-0.76487083]
 [-0.05382362]
 [ 2.61037559]
 [-0.04796655]
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 [-1.90137395]]
[[ -1.80420038e-02  -3.02637682e-01   2.68415885e-01 ...,  -2.31229792e-01
   -3.38610353e-01   2.75502458e-01]
 [  5.86220843e-02   1.46977978e-01   2.68720094e-03 ...,  -2.21837930e-01
    1.59230774e+00   1.14866137e-01]
 [ -6.15276667e-02   2.56765625e-01   4.67051207e-01 ...,   2.33929890e-01
   -3.06329036e-01   9.65652094e-01]
 ..., 
 [ -1.84675684e-01  -2.40716295e-01  -3.80726157e-01 ...,   8.96373279e-02
   -5.98863471e-01  -3.20561400e-01]
 [ -2.75842259e-01  -1.85483678e-01  -1.85432633e-01 ...,  -1.18802205e-01
   -1.54239156e-01  -3.44857612e-01]
 [  3.91883652e-02   8.52385874e-02  -4.23939229e-02 ...,   5.38229091e-02
    2.89486031e+00  -6.56027922e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.15987925]
 [-0.94460842]
 [-1.18882146]
 [-0.76467073]
 [-0.05426236]
 [ 2.61127577]
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 [ 0.14723616]
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 [ 4.4699001 ]
 [-0.94519092]
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 [ 0.38643819]
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 [-1.90014081]]
[[ -1.80358699e-02  -3.02675682e-01   2.68587779e-01 ...,  -2.31217103e-01
   -3.38262728e-01   2.75019043e-01]
 [  5.85549666e-02   1.46573198e-01   2.20367242e-03 ...,  -2.21954772e-01
    1.59351728e+00   1.14039286e-01]
 [ -6.17186490e-02   2.55732085e-01   4.65534562e-01 ...,   2.33605241e-01
   -3.03010977e-01   9.63889573e-01]
 ..., 
 [ -1.84634564e-01  -2.40549891e-01  -3.80488176e-01 ...,   8.97146010e-02
   -6.00162903e-01  -3.20330261e-01]
 [ -2.75772329e-01  -1.85145832e-01  -1.84980231e-01 ...,  -1.18672477e-01
   -1.54552622e-01  -3.44709510e-01]
 [  3.91363035e-02   8.49287990e-02  -4.26405807e-02 ...,   5.37241308e-02
    2.89498262e+00  -6.60526296e-02]]
Progress: 78.4% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16261368]
 [-0.947012  ]
 [-1.18994181]
 [-0.76755363]
 [-0.0569305 ]
 [ 2.6098966 ]
 [-0.04995028]
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 [ 4.47035728]
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[[ -1.79565571e-02  -3.02275483e-01   2.68830188e-01 ...,  -2.31071810e-01
   -3.40809919e-01   2.75688255e-01]
 [  5.86251089e-02   1.46967895e-01   2.57622335e-03 ...,  -2.21827571e-01
    1.59306899e+00   1.14473034e-01]
 [ -6.16041488e-02   2.56348913e-01   4.66571838e-01 ...,   2.33808397e-01
   -3.07397577e-01   9.65158687e-01]
 ..., 
 [ -1.84590055e-01  -2.40316221e-01  -3.80134544e-01 ...,   8.97923572e-02
   -6.00356118e-01  -3.20033409e-01]
 [ -2.75789020e-01  -1.85248020e-01  -1.85069621e-01 ...,  -1.18693136e-01
   -1.54968171e-01  -3.44894748e-01]
 [  3.92311860e-02   8.54738495e-02  -4.20502193e-02 ...,   5.39028222e-02
    2.89494161e+00  -6.54512468e-02]]
Progress: 78.5% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16069901]
 [-0.94593806]
 [-1.18952468]
 [-0.76720053]
 [-0.05678042]
 [ 2.61376065]
 [-0.04820409]
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 [ 0.14680601]
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 [ 0.87521989]
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 [ 0.14163084]
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 [ 4.47079279]
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 [-1.64579838]
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 [-0.30577463]
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 [-1.89932188]]
[[ -1.81888871e-02  -3.03591814e-01   2.67564447e-01 ...,  -2.31491932e-01
   -3.39803394e-01   2.73034827e-01]
 [  5.86286736e-02   1.46985055e-01   2.58581539e-03 ...,  -2.21822353e-01
    1.59306389e+00   1.14481091e-01]
 [ -6.19440424e-02   2.54468166e-01   4.65285182e-01 ...,   2.33232058e-01
   -3.02068847e-01   9.62423890e-01]
 ..., 
 [ -1.84646583e-01  -2.40621124e-01  -3.80698581e-01 ...,   8.97000577e-02
   -5.99057563e-01  -3.20512028e-01]
 [ -2.75734016e-01  -1.84954000e-01  -1.84687911e-01 ...,  -1.18604412e-01
   -1.54906345e-01  -3.44865686e-01]
 [  3.92813521e-02   8.57573607e-02  -4.16873384e-02 ...,   5.39955837e-02
    2.89475824e+00  -6.48589559e-02]]
Progress: 78.5% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16536943]
 [-0.94950216]
 [-1.19512982]
 [-0.76976889]
 [-0.05930109]
 [ 2.61043037]
 [-0.05165054]
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 [ 0.14299654]
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 [ 0.87018193]
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[[-0.01793416 -0.30212738  0.26940133 ..., -0.23103291 -0.34233755
   0.27598951]
 [ 0.05868253  0.14729086  0.00291451 ..., -0.22172573  1.592724
   0.11483265]
 [-0.06157466  0.25667628  0.46754207 ...,  0.2339237  -0.30664316
   0.96706836]
 ..., 
 [-0.18464006 -0.24060149 -0.38062535 ...,  0.08970782 -0.59871085
  -0.32061773]
 [-0.27560687 -0.18427951 -0.18403237 ..., -0.11839482 -0.15809961
  -0.3439557 ]
 [ 0.0392667   0.08566232 -0.04189351 ...,  0.05395618  2.89464205
  -0.06459949]]
Progress: 78.5% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16137455]
 [-0.94600001]
 [-1.18923184]
 [-0.76775868]
 [-0.05607823]
 [ 2.61197678]
 [-0.04841441]
 [-1.09050677]
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 [ 4.29042662]
 [-1.90168588]]
[[-0.0181063  -0.3030588   0.26831821 ..., -0.23133597 -0.33796988
   0.27451432]
 [ 0.05867397  0.14724384  0.00290009 ..., -0.22174081  1.59275271
   0.11479929]
 [-0.06170531  0.25585667  0.46660185 ...,  0.23368858 -0.30261907
   0.96444493]
 ..., 
 [-0.18464311 -0.24064464 -0.38095273 ...,  0.08970447 -0.59810714
  -0.32062007]
 [-0.27560022 -0.18424395 -0.18419283 ..., -0.11838362 -0.15819331
  -0.34383067]
 [ 0.03931033  0.085869   -0.04171404 ...,  0.05403268  2.8946018
  -0.06436008]]
Progress: 78.5% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.1655178 ]
 [-0.94964391]
 [-1.19243147]
 [-0.77070003]
 [-0.05772897]
 [ 2.60849467]
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 [ 1.01442925]
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[[-0.01799936 -0.30245939  0.2691653  ..., -0.2311489  -0.33947453
   0.27563383]
 [ 0.05867397  0.14724384  0.00290009 ..., -0.22174081  1.59275271
   0.11479929]
 [-0.06134946  0.25791523  0.4694268  ...,  0.23434983 -0.30503665
   0.96820904]
 ..., 
 [-0.18447368 -0.23966715 -0.37975904 ...,  0.09001754 -0.59985576
  -0.31939954]
 [-0.2755021  -0.1837045  -0.18340346 ..., -0.1182062  -0.15877234
  -0.34278429]
 [ 0.0393708   0.08623292 -0.0415156  ...,  0.05414766  2.89456157
  -0.06391184]]
Progress: 78.5% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.15670506]
 [-0.94151291]
 [-1.18524516]
 [-0.76312613]
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 [ 2.61417483]
 [-0.04522582]
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 [ 0.88137329]
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[[ -1.84109850e-02  -3.04785916e-01   2.66771585e-01 ...,  -2.31893881e-01
   -3.33739722e-01   2.71987717e-01]
 [  5.86473357e-02   1.47088181e-01   2.73760372e-03 ...,  -2.21790620e-01
    1.59282673e+00   1.14552844e-01]
 [ -6.16877312e-02   2.56051529e-01   4.67132871e-01 ...,   2.33770585e-01
   -3.00610965e-01   9.64185004e-01]
 ..., 
 [ -1.84538959e-01  -2.40026281e-01  -3.80077559e-01 ...,   8.99035942e-02
   -5.98447093e-01  -3.19909817e-01]
 [ -2.75455469e-01  -1.83466362e-01  -1.83021731e-01 ...,  -1.18141347e-01
   -1.59439709e-01  -3.42287088e-01]
 [  3.92884901e-02   8.57828532e-02  -4.19897184e-02 ...,   5.39929261e-02
    2.89458351e+00  -6.46062551e-02]]
Progress: 78.5% ... Training loss: 0.069 ... Validation loss: 0.149[[-0.16673004]
 [-0.95046888]
 [-1.19471375]
 [-0.77141146]
 [-0.05812145]
 [ 2.61088325]
 [-0.05362602]
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 [ 4.46901   ]
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 [-1.90536084]]
[[ -1.81153961e-02  -3.03161819e-01   2.68509310e-01 ...,  -2.31383747e-01
   -3.38983995e-01   2.74655980e-01]
 [  5.86576494e-02   1.47133472e-01   2.66311999e-03 ...,  -2.21777136e-01
    1.59269733e+00   1.14559812e-01]
 [ -6.14412675e-02   2.57585250e-01   4.69330227e-01 ...,   2.34236784e-01
   -3.05440625e-01   9.67910101e-01]
 ..., 
 [ -1.84353393e-01  -2.38973633e-01  -3.79181274e-01 ...,   9.02391365e-02
   -6.00746888e-01  -3.18873666e-01]
 [ -2.75264948e-01  -1.82417426e-01  -1.81670946e-01 ...,  -1.17807196e-01
   -1.62068345e-01  -3.40655883e-01]
 [  3.92173262e-02   8.53597105e-02  -4.25392983e-02 ...,   5.38540047e-02
    2.89505001e+00  -6.57282178e-02]]
Progress: 78.5% ... Training loss: 0.065 ... Validation loss: 0.140[[-0.1583356 ]
 [-0.94262678]
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 [ 4.47173279]
 [-0.94347256]
 [-1.64323108]
 [ 0.3886333 ]
 [-0.30313209]
 [ 4.29457516]
 [-1.9008926 ]]
[[ -1.84425578e-02  -3.04932200e-01   2.66462618e-01 ...,  -2.31949921e-01
   -3.34948741e-01   2.72008707e-01]
 [  5.86212980e-02   1.46924724e-01   2.40533313e-03 ...,  -2.21844856e-01
    1.59300686e+00   1.14363456e-01]
 [ -6.16798762e-02   2.56223922e-01   4.67606937e-01 ...,   2.33801306e-01
   -3.01069925e-01   9.64100631e-01]
 ..., 
 [ -1.84412927e-01  -2.39306816e-01  -3.79447542e-01 ...,   9.01401411e-02
   -6.00002857e-01  -3.19653033e-01]
 [ -2.75410285e-01  -1.83244043e-01  -1.82487497e-01 ...,  -1.18052832e-01
   -1.61022933e-01  -3.41802005e-01]
 [  3.91455826e-02   8.49638130e-02  -4.30855664e-02 ...,   5.37148937e-02
    2.89517393e+00  -6.60527044e-02]]
Progress: 78.5% ... Training loss: 0.066 ... Validation loss: 0.146[[-0.16450866]
 [-0.94828738]
 [-1.19128935]
 [-0.77080232]
 [-0.0562618 ]
 [ 2.60926443]
 [-0.0523275 ]
 [-1.09074479]
 [-0.52691263]
 [ 1.01348018]
 [-0.09252568]
 [ 0.14484036]
 [-0.10554159]
 [-0.99399802]
 [-0.29435666]
 [ 0.87437008]
 [-0.8359531 ]
 [-0.79261998]
 [-0.61562309]
 [ 0.14043856]
 [-0.34904521]
 [ 4.47220989]
 [-0.94999219]
 [-1.64583681]
 [ 0.38404634]
 [-0.30968368]
 [ 4.28571157]
 [-1.90481576]]
[[ -1.84585644e-02  -3.05102364e-01   2.66215464e-01 ...,  -2.31965325e-01
   -3.36885803e-01   2.71549954e-01]
 [  5.85513280e-02   1.46512359e-01   1.90751816e-03 ...,  -2.21972019e-01
    1.59303197e+00   1.13776863e-01]
 [ -6.12493528e-02   2.58689540e-01   4.70487959e-01 ...,   2.34630746e-01
   -3.08175118e-01   9.69622009e-01]
 ..., 
 [ -1.84283190e-01  -2.38586406e-01  -3.78699743e-01 ...,   9.03825872e-02
   -6.02732887e-01  -3.18466908e-01]
 [ -2.75482806e-01  -1.83643348e-01  -1.82765130e-01 ...,  -1.18144191e-01
   -1.60988678e-01  -3.42135641e-01]
 [  3.93285834e-02   8.60299402e-02  -4.21569600e-02 ...,   5.40635757e-02
    2.89484716e+00  -6.45332130e-02]]
Progress: 78.5% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.1593003 ]
 [-0.94350153]
 [-1.18561107]
 [-0.76705246]
 [-0.05306531]
 [ 2.61166098]
 [-0.0484248 ]
 [-1.08797498]
 [-0.52197935]
 [ 1.01782095]
 [-0.08766071]
 [ 0.14932702]
 [-0.10156328]
 [-0.99144653]
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 [ 0.87974012]
 [-0.82980517]
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 [ 0.14430336]
 [-0.34502409]
 [ 4.47335821]
 [-0.94705692]
 [-1.64150965]
 [ 0.38720462]
 [-0.30551636]
 [ 4.29478687]
 [-1.90290384]]
[[ -1.86038371e-02  -3.05928107e-01   2.65432381e-01 ...,  -2.32220814e-01
   -3.36374737e-01   2.70762120e-01]
 [  5.85694892e-02   1.46612044e-01   2.01754204e-03 ...,  -2.21939446e-01
    1.59294889e+00   1.13904336e-01]
 [ -6.14121844e-02   2.57757087e-01   4.69443881e-01 ...,   2.34311500e-01
   -3.05522139e-01   9.67712039e-01]
 ..., 
 [ -1.84342202e-01  -2.38906941e-01  -3.78999392e-01 ...,   9.02759331e-02
   -6.02084534e-01  -3.19023862e-01]
 [ -2.75469346e-01  -1.83551916e-01  -1.82602622e-01 ...,  -1.18110338e-01
   -1.61464779e-01  -3.41650164e-01]
 [  3.93276524e-02   8.59966374e-02  -4.22149115e-02 ...,   5.40658823e-02
    2.89484031e+00  -6.42583905e-02]]
Progress: 78.5% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.16449643]
 [-0.94852806]
 [-1.1900778 ]
 [-0.77164192]
 [-0.05876884]
 [ 2.60950504]
 [-0.05338841]
 [-1.09271616]
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 [ 1.01400425]
 [-0.09333571]
 [ 0.14364207]
 [-0.10719686]
 [-0.99432038]
 [-0.29485029]
 [ 0.87284536]
 [-0.83511983]
 [-0.79203082]
 [-0.61569185]
 [ 0.13929601]
 [-0.35023512]
 [ 4.47262341]
 [-0.95053252]
 [-1.64644358]
 [ 0.3826739 ]
 [-0.31034692]
 [ 4.28619917]
 [-1.90410405]]
[[ -1.84006919e-02  -3.04875893e-01   2.66382036e-01 ...,  -2.31843361e-01
   -3.40536249e-01   2.71809489e-01]
 [  5.85839547e-02   1.46669796e-01   2.20195342e-03 ...,  -2.21910275e-01
    1.59274033e+00   1.14086591e-01]
 [ -6.13808028e-02   2.57946703e-01   4.69916542e-01 ...,   2.34352722e-01
   -3.09100681e-01   9.68162740e-01]
 ..., 
 [ -1.84276215e-01  -2.38537528e-01  -3.79047796e-01 ...,   9.04096876e-02
   -6.03082967e-01  -3.18708696e-01]
 [ -2.75378016e-01  -1.83123975e-01  -1.82229487e-01 ...,  -1.17953263e-01
   -1.63576017e-01  -3.41485432e-01]
 [  3.93998345e-02   8.64709245e-02  -4.17206462e-02 ...,   5.42082213e-02
    2.89467951e+00  -6.39194498e-02]]
Progress: 78.5% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.15866781]
 [-0.94396458]
 [-1.18493772]
 [-0.76765431]
 [-0.05414028]
 [ 2.61288684]
 [-0.04787242]
 [-1.08997934]
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 [ 1.01814962]
 [-0.08860991]
 [ 0.14895588]
 [-0.10171638]
 [-0.98924653]
 [-0.28906962]
 [ 0.87914115]
 [-0.82957387]
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 [-0.61031934]
 [ 0.14391831]
 [-0.3451459 ]
 [ 4.47358462]
 [-0.94700886]
 [-1.64234454]
 [ 0.38810072]
 [-0.3057214 ]
 [ 4.29459213]
 [-1.90054347]]
[[ -1.86366005e-02  -3.06144012e-01   2.64815272e-01 ...,  -2.32270139e-01
   -3.35417097e-01   2.69236370e-01]
 [  5.84997365e-02   1.46195011e-01   1.59764113e-03 ...,  -2.22063581e-01
    1.59436625e+00   1.13372361e-01]
 [ -6.16911040e-02   2.56080219e-01   4.67771169e-01 ...,   2.33795080e-01
   -3.04023428e-01   9.64274035e-01]
 ..., 
 [ -1.84359459e-01  -2.38956535e-01  -3.79574149e-01 ...,   9.02691112e-02
   -6.01113529e-01  -3.19295594e-01]
 [ -2.75630025e-01  -1.84560111e-01  -1.83878541e-01 ...,  -1.18406436e-01
   -1.60060561e-01  -3.43769875e-01]
 [  3.93754342e-02   8.63127124e-02  -4.18943458e-02 ...,   5.41575000e-02
    2.89468986e+00  -6.41382078e-02]]
Progress: 78.5% ... Training loss: 0.065 ... Validation loss: 0.144[[-0.16222748]
 [-0.94680934]
 [-1.18605033]
 [-0.77174314]
 [-0.05752478]
 [ 2.61023871]
 [-0.05145763]
 [-1.09305697]
 [-0.52316619]
 [ 1.01670656]
 [-0.09195625]
 [ 0.14567033]
 [-0.10499414]
 [-0.99238476]
 [-0.29207826]
 [ 0.87569   ]
 [-0.83276062]
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 [ 0.14102247]
 [-0.3480779 ]
 [ 4.47306401]
 [-0.9504819 ]
 [-1.64480299]
 [ 0.38515811]
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 [ 4.28975266]
 [-1.90250463]]
[[ -1.84937183e-02  -3.05433747e-01   2.65403702e-01 ...,  -2.32025677e-01
   -3.38077476e-01   2.70631617e-01]
 [  5.85060295e-02   1.46232643e-01   1.64838701e-03 ...,  -2.22050717e-01
    1.59433138e+00   1.13444547e-01]
 [ -6.16257130e-02   2.56392151e-01   4.68619544e-01 ...,   2.33924106e-01
   -3.08605902e-01   9.66020716e-01]
 ..., 
 [ -1.84287824e-01  -2.38599402e-01  -3.79115145e-01 ...,   9.04051611e-02
   -6.02752334e-01  -3.18610360e-01]
 [ -2.75633740e-01  -1.84613663e-01  -1.83926646e-01 ...,  -1.18418159e-01
   -1.59984860e-01  -3.43534450e-01]
 [  3.93547440e-02   8.61942199e-02  -4.21081352e-02 ...,   5.41135289e-02
    2.89470040e+00  -6.44730134e-02]]
Progress: 78.5% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16006773]
 [-0.94455213]
 [-1.18465054]
 [-0.76918382]
 [-0.05649271]
 [ 2.61273857]
 [-0.04949056]
 [-1.09297995]
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 [ 1.01727149]
 [-0.09067479]
 [ 0.14731579]
 [-0.10292138]
 [-0.99064906]
 [-0.29010722]
 [ 0.87717373]
 [-0.83070573]
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 [-0.61077455]
 [ 0.14300927]
 [-0.34627921]
 [ 4.47357897]
 [-0.94834333]
 [-1.64432006]
 [ 0.38675283]
 [-0.30673877]
 [ 4.29347525]
 [-1.90104601]]
[[ -1.85978055e-02  -3.06050294e-01   2.64862014e-01 ...,  -2.32225987e-01
   -3.37040847e-01   2.69208346e-01]
 [  5.85374735e-02   1.46413674e-01   1.83318343e-03 ...,  -2.21992297e-01
    1.59412521e+00   1.13772397e-01]
 [ -6.18441128e-02   2.55280858e-01   4.67029854e-01 ...,   2.33531775e-01
   -3.06255342e-01   9.63900916e-01]
 ..., 
 [ -1.84325826e-01  -2.38816689e-01  -3.79268245e-01 ...,   9.03375403e-02
   -6.02073023e-01  -3.18903583e-01]
 [ -2.75637736e-01  -1.84645622e-01  -1.83993779e-01 ...,  -1.18422840e-01
   -1.59080127e-01  -3.43829673e-01]
 [  3.94274584e-02   8.66366524e-02  -4.15302536e-02 ...,   5.42534480e-02
    2.89464845e+00  -6.40066972e-02]]
Progress: 78.5% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16553781]
 [-0.94792146]
 [-1.18880385]
 [-0.77228285]
 [-0.05941279]
 [ 2.60979461]
 [-0.05339252]
 [-1.09572213]
 [-0.52517127]
 [ 1.01352153]
 [-0.09443481]
 [ 0.14293314]
 [-0.1074091 ]
 [-0.99462449]
 [-0.29403216]
 [ 0.87161786]
 [-0.83532331]
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 [ 0.13918172]
 [-0.35076308]
 [ 4.47224573]
 [-0.95295647]
 [-1.64859316]
 [ 0.38284146]
 [-0.31027548]
 [ 4.28631426]
 [-1.90353808]]
[[ -1.83388989e-02  -3.04632177e-01   2.66284708e-01 ...,  -2.31755320e-01
   -3.40342183e-01   2.71184926e-01]
 [  5.84884627e-02   1.46137706e-01   1.60804536e-03 ...,  -2.22089553e-01
    1.59411780e+00   1.13511248e-01]
 [ -6.17370084e-02   2.55990659e-01   4.68075828e-01 ...,   2.33754190e-01
   -3.08882799e-01   9.65986809e-01]
 ..., 
 [ -1.84180048e-01  -2.38006419e-01  -3.78447831e-01 ...,   9.06108753e-02
   -6.04631555e-01  -3.17744303e-01]
 [ -2.75653984e-01  -1.84773492e-01  -1.84127567e-01 ...,  -1.18461632e-01
   -1.59307961e-01  -3.43796036e-01]
 [  3.94673246e-02   8.68688030e-02  -4.12736698e-02 ...,   5.43336924e-02
    2.89459810e+00  -6.37497716e-02]]
Progress: 78.5% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16279739]
 [-0.9466781 ]
 [-1.18935348]
 [-0.76931575]
 [-0.05751134]
 [ 2.61034016]
 [-0.05134233]
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 [ 1.01404989]
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 [ 0.14497607]
 [-0.10487936]
 [-0.99379477]
 [-0.29235473]
 [ 0.87347392]
 [-0.83343539]
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 [-0.61421825]
 [ 0.1414229 ]
 [-0.34838266]
 [ 4.47228585]
 [-0.94960424]
 [-1.64511261]
 [ 0.38392599]
 [-0.30849685]
 [ 4.29034861]
 [-1.90391253]]
[[ -1.84514743e-02  -3.05200586e-01   2.65466012e-01 ...,  -2.31971121e-01
   -3.39563554e-01   2.71239939e-01]
 [  5.84430678e-02   1.45918061e-01   1.49103385e-03 ...,  -2.22165434e-01
    1.59451052e+00   1.13348473e-01]
 [ -6.14325376e-02   2.57601030e-01   4.69307317e-01 ...,   2.34291079e-01
   -3.11376014e-01   9.67587677e-01]
 ..., 
 [ -1.84247587e-01  -2.38381087e-01  -3.78799334e-01 ...,   9.04885151e-02
   -6.03683445e-01  -3.18315654e-01]
 [ -2.75499520e-01  -1.83894580e-01  -1.83294573e-01 ...,  -1.18196672e-01
   -1.60159959e-01  -3.42380871e-01]
 [  3.94557447e-02   8.68315228e-02  -4.14769493e-02 ...,   5.43066639e-02
    2.89466441e+00  -6.36820378e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16266818]
 [-0.94586651]
 [-1.18821178]
 [-0.76913181]
 [-0.05750299]
 [ 2.6093342 ]
 [-0.05161158]
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 [-0.52410708]
 [ 1.01449942]
 [-0.09110684]
 [ 0.14505151]
 [-0.10525125]
 [-0.99486878]
 [-0.29155781]
 [ 0.87351935]
 [-0.83226414]
 [-0.79054137]
 [-0.61308778]
 [ 0.14164262]
 [-0.34853673]
 [ 4.47235188]
 [-0.95052618]
 [-1.64459312]
 [ 0.38340701]
 [-0.30779907]
 [ 4.29206311]
 [-1.9037937 ]]
[[ -1.83678502e-02  -3.04760031e-01   2.65875253e-01 ...,  -2.31833025e-01
   -3.42524992e-01   2.72366988e-01]
 [  5.84333670e-02   1.45860555e-01   1.51291701e-03 ...,  -2.22184177e-01
    1.59452732e+00   1.13347681e-01]
 [ -6.14379879e-02   2.57549945e-01   4.69192871e-01 ...,   2.34274701e-01
   -3.13199290e-01   9.67193772e-01]
 ..., 
 [ -1.84283365e-01  -2.38549225e-01  -3.79019655e-01 ...,   9.04239103e-02
   -6.02928931e-01  -3.18471723e-01]
 [ -2.75489279e-01  -1.83848844e-01  -1.83226778e-01 ...,  -1.18182702e-01
   -1.60511946e-01  -3.42265428e-01]
 [  3.93760785e-02   8.63891738e-02  -4.20102064e-02 ...,   5.41528141e-02
    2.89475494e+00  -6.43638278e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16535018]
 [-0.94883249]
 [-1.19020921]
 [-0.77181699]
 [-0.05939455]
 [ 2.60862387]
 [-0.0536742 ]
 [-1.09432368]
 [-0.52612406]
 [ 1.0132984 ]
 [-0.09321477]
 [ 0.14262526]
 [-0.10721048]
 [-0.99517111]
 [-0.29437726]
 [ 0.87022592]
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 [-0.35115707]
 [ 4.47240969]
 [-0.95086901]
 [-1.64772144]
 [ 0.38154551]
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 [ 4.28631994]
 [-1.90450259]]
[[ -1.82206855e-02  -3.03917066e-01   2.66937642e-01 ...,  -2.31558382e-01
   -3.41772042e-01   2.73544859e-01]
 [  5.85041844e-02   1.46269762e-01   1.74003027e-03 ...,  -2.22053602e-01
    1.59438494e+00   1.13868802e-01]
 [ -6.14212071e-02   2.57589586e-01   4.69389162e-01 ...,   2.34276205e-01
   -3.11183677e-01   9.66912949e-01]
 ..., 
 [ -1.84291021e-01  -2.38588265e-01  -3.79171767e-01 ...,   9.04235292e-02
   -6.01531972e-01  -3.18768639e-01]
 [ -2.75550784e-01  -1.84193535e-01  -1.83475507e-01 ...,  -1.18277553e-01
   -1.58893609e-01  -3.42956781e-01]
 [  3.93649571e-02   8.63410450e-02  -4.22396858e-02 ...,   5.41350280e-02
    2.89480506e+00  -6.44444538e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16170888]
 [-0.94554803]
 [-1.18717336]
 [-0.768948  ]
 [-0.05662832]
 [ 2.61226619]
 [-0.05043939]
 [-1.09309552]
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 [ 1.01503378]
 [-0.09058575]
 [ 0.1452744 ]
 [-0.10416878]
 [-0.99207994]
 [-0.29074247]
 [ 0.87374386]
 [-0.83146786]
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 [ 0.14307749]
 [-0.3490232 ]
 [ 4.47228666]
 [-0.94820346]
 [-1.64611648]
 [ 0.38503526]
 [-0.30624389]
 [ 4.29263234]
 [-1.90207956]]
[[ -1.83577005e-02  -3.04699253e-01   2.66324163e-01 ...,  -2.31826386e-01
   -3.40667829e-01   2.71858982e-01]
 [  5.84954024e-02   1.46203676e-01   1.67181728e-03 ...,  -2.22074998e-01
    1.59511026e+00   1.13735860e-01]
 [ -6.17053018e-02   2.55956629e-01   4.67591330e-01 ...,   2.33744337e-01
   -3.07638834e-01   9.63672449e-01]
 ..., 
 [ -1.84314538e-01  -2.38710735e-01  -3.79395588e-01 ...,   9.03796969e-02
   -6.00781278e-01  -3.18920001e-01]
 [ -2.75583861e-01  -1.84358601e-01  -1.83589618e-01 ...,  -1.18337057e-01
   -1.58607798e-01  -3.43148263e-01]
 [  3.93397235e-02   8.62253395e-02  -4.25186085e-02 ...,   5.40887388e-02
    2.89497294e+00  -6.49587283e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16156864]
 [-0.94622539]
 [-1.18730412]
 [-0.76872688]
 [-0.05771904]
 [ 2.61437486]
 [-0.05002365]
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 [ 1.01436937]
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 [ 0.14516597]
 [-0.10370012]
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 [ 0.87317502]
 [-0.83175838]
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 [-0.61364798]
 [ 0.14262016]
 [-0.34959926]
 [ 4.47261945]
 [-0.94631895]
 [-1.64637615]
 [ 0.38541655]
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 [ 4.29321779]
 [-1.90111387]]
[[ -1.84632110e-02  -3.05244704e-01   2.65919608e-01 ...,  -2.32009888e-01
   -3.39405682e-01   2.71247476e-01]
 [  5.84873989e-02   1.46157238e-01   1.65583728e-03 ...,  -2.22090062e-01
    1.59516355e+00   1.13692682e-01]
 [ -6.17417601e-02   2.55673035e-01   4.67585606e-01 ...,   2.33655600e-01
   -3.06599571e-01   9.62633655e-01]
 ..., 
 [ -1.84396433e-01  -2.39155737e-01  -3.79827479e-01 ...,   9.02362913e-02
   -5.99447489e-01  -3.19426502e-01]
 [ -2.75606049e-01  -1.84504049e-01  -1.83802912e-01 ...,  -1.18369811e-01
   -1.57699709e-01  -3.43789214e-01]
 [  3.93357094e-02   8.62233050e-02  -4.23473872e-02 ...,   5.40775310e-02
    2.89514648e+00  -6.49215205e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16548582]
 [-0.94919336]
 [-1.19045642]
 [-0.77192297]
 [-0.06080598]
 [ 2.61190462]
 [-0.05368268]
 [-1.09583709]
 [-0.52716149]
 [ 1.01197499]
 [-0.09393663]
 [ 0.14185591]
 [-0.10730617]
 [-0.99411209]
 [-0.29504531]
 [ 0.86925294]
 [-0.83544454]
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 [ 0.13939497]
 [-0.35272554]
 [ 4.47136058]
 [-0.94952107]
 [-1.64892878]
 [ 0.38234009]
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 [ 4.28775852]
 [-1.90349661]]
[[ -1.82689413e-02  -3.04110883e-01   2.67052701e-01 ...,  -2.31648228e-01
   -3.42706012e-01   2.73345536e-01]
 [  5.85189347e-02   1.46339543e-01   1.81397813e-03 ...,  -2.22033747e-01
    1.59500433e+00   1.13934109e-01]
 [ -6.15922950e-02   2.56524885e-01   4.68755289e-01 ...,   2.33942707e-01
   -3.10072817e-01   9.65129207e-01]
 ..., 
 [ -1.84348077e-01  -2.38879316e-01  -3.79607122e-01 ...,   9.03295191e-02
   -5.99965561e-01  -3.19004355e-01]
 [ -2.75497378e-01  -1.83917262e-01  -1.83100997e-01 ...,  -1.18183050e-01
   -1.59287320e-01  -3.43116539e-01]
 [  3.92889286e-02   8.59673184e-02  -4.26868604e-02 ...,   5.39921544e-02
    2.89521634e+00  -6.53764860e-02]]
Progress: 78.6% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16227057]
 [-0.94620483]
 [-1.18767373]
 [-0.76876656]
 [-0.05755433]
 [ 2.61265368]
 [-0.05080416]
 [-1.09322689]
 [-0.52384696]
 [ 1.01490775]
 [-0.09062743]
 [ 0.14461999]
 [-0.10418598]
 [-0.99194531]
 [-0.2919872 ]
 [ 0.87273888]
 [-0.83224395]
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 [ 0.14216685]
 [-0.34990707]
 [ 4.47187954]
 [-0.94708668]
 [-1.64582361]
 [ 0.38451728]
 [-0.30669005]
 [ 4.29243442]
 [-1.90203359]]
[[ -1.82774013e-02  -3.04121439e-01   2.66986542e-01 ...,  -2.31673282e-01
   -3.41629054e-01   2.73178761e-01]
 [  5.84939161e-02   1.46208082e-01   1.57459380e-03 ...,  -2.22078278e-01
    1.59522645e+00   1.13656361e-01]
 [ -6.15957694e-02   2.56504486e-01   4.68083258e-01 ...,   2.33939875e-01
   -3.08958928e-01   9.63917561e-01]
 ..., 
 [ -1.84371971e-01  -2.39016590e-01  -3.79649166e-01 ...,   9.02835328e-02
   -5.99911646e-01  -3.19036049e-01]
 [ -2.75558362e-01  -1.84252610e-01  -1.83422554e-01 ...,  -1.18294417e-01
   -1.58035616e-01  -3.43827202e-01]
 [  3.93126639e-02   8.61302485e-02  -4.26734278e-02 ...,   5.40209494e-02
    2.89518857e+00  -6.51408997e-02]]
Progress: 78.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.1641127 ]
 [-0.94635393]
 [-1.18768802]
 [-0.76995085]
 [-0.05868138]
 [ 2.61260116]
 [-0.05194448]
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 [ 1.01450586]
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 [ 0.14275599]
 [-0.10574448]
 [-0.99218703]
 [-0.29299714]
 [ 0.87045707]
 [-0.83343492]
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 [-0.61406011]
 [ 0.14093209]
 [-0.35163555]
 [ 4.47161066]
 [-0.94854214]
 [-1.64838576]
 [ 0.38344477]
 [-0.3072737 ]
 [ 4.29034032]
 [-1.90224249]]
[[ -1.81751561e-02  -3.03537045e-01   2.67499537e-01 ...,  -2.31496771e-01
   -3.42755332e-01   2.74239422e-01]
 [  5.84867930e-02   1.46171096e-01   1.53446938e-03 ...,  -2.22092075e-01
    1.59532974e+00   1.13570183e-01]
 [ -6.17751955e-02   2.55469386e-01   4.66875244e-01 ...,   2.33610695e-01
   -3.08439819e-01   9.62921086e-01]
 ..., 
 [ -1.84371678e-01  -2.39021397e-01  -3.79671292e-01 ...,   9.02892498e-02
   -6.00212061e-01  -3.19029453e-01]
 [ -2.75577246e-01  -1.84330786e-01  -1.83612964e-01 ...,  -1.18341088e-01
   -1.58617165e-01  -3.43779281e-01]
 [  3.93577562e-02   8.63796087e-02  -4.23595545e-02 ...,   5.41001656e-02
    2.89506504e+00  -6.50047298e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16221256]
 [-0.94460886]
 [-1.18749695]
 [-0.76795655]
 [-0.05606028]
 [ 2.61367192]
 [-0.04953033]
 [-1.09343   ]
 [-0.52264158]
 [ 1.01576005]
 [-0.08965292]
 [ 0.1446171 ]
 [-0.10384032]
 [-0.99020078]
 [-0.29143283]
 [ 0.87172266]
 [-0.83182982]
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 [-0.61347267]
 [ 0.14242672]
 [-0.35082982]
 [ 4.47298182]
 [-0.94645737]
 [-1.64751632]
 [ 0.38507105]
 [-0.30558455]
 [ 4.29307872]
 [-1.90104548]]
[[ -1.82328396e-02  -3.03858877e-01   2.67211514e-01 ...,  -2.31606181e-01
   -3.40933806e-01   2.73877602e-01]
 [  5.83802688e-02   1.45559830e-01   9.03921031e-04 ...,  -2.22283212e-01
    1.59669113e+00   1.12458324e-01]
 [ -6.18250018e-02   2.55150402e-01   4.66318089e-01 ...,   2.33525563e-01
   -3.07814035e-01   9.61372475e-01]
 ..., 
 [ -1.84389241e-01  -2.39116058e-01  -3.79834930e-01 ...,   9.02560434e-02
   -5.99809303e-01  -3.19363833e-01]
 [ -2.75601766e-01  -1.84474005e-01  -1.83700767e-01 ...,  -1.18376020e-01
   -1.58517461e-01  -3.44252399e-01]
 [  3.93890446e-02   8.65443527e-02  -4.21851887e-02 ...,   5.41470821e-02
    2.89497037e+00  -6.49079807e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16605473]
 [-0.94806715]
 [-1.19028853]
 [-0.77122149]
 [-0.05890315]
 [ 2.60965042]
 [-0.05290587]
 [-1.09503222]
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 [ 1.01446602]
 [-0.09271586]
 [ 0.14115949]
 [-0.10723648]
 [-0.99411147]
 [-0.29517469]
 [ 0.86825955]
 [-0.83590645]
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 [ 0.13924988]
 [-0.35397994]
 [ 4.47341638]
 [-0.94914504]
 [-1.64943535]
 [ 0.381557  ]
 [-0.30886055]
 [ 4.28642991]
 [-1.90390235]]
[[ -1.80075659e-02  -3.02532182e-01   2.68554210e-01 ...,  -2.31169580e-01
   -3.42252091e-01   2.75992952e-01]
 [  5.84796056e-02   1.46142241e-01   1.51483608e-03 ...,  -2.22099387e-01
    1.59549279e+00   1.13534733e-01]
 [ -6.15065870e-02   2.57088170e-01   4.68468958e-01 ...,   2.34148621e-01
   -3.10382043e-01   9.64806876e-01]
 ..., 
 [ -1.84381579e-01  -2.39053490e-01  -3.79773868e-01 ...,   9.02766926e-02
   -5.99673181e-01  -3.19500984e-01]
 [ -2.75572659e-01  -1.84320464e-01  -1.83520264e-01 ...,  -1.18318044e-01
   -1.59295102e-01  -3.43936368e-01]
 [  3.94262732e-02   8.67466170e-02  -4.17696082e-02 ...,   5.42142325e-02
    2.89478166e+00  -6.46996290e-02]]
Progress: 78.6% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16095947]
 [-0.94376358]
 [-1.18708204]
 [-0.76605551]
 [-0.05388059]
 [ 2.61135442]
 [-0.04850726]
 [-1.08953374]
 [-0.52266605]
 [ 1.01810676]
 [-0.08779256]
 [ 0.14594205]
 [-0.10295292]
 [-0.99245493]
 [-0.29037406]
 [ 0.87413466]
 [-0.83102167]
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 [ 0.14351687]
 [-0.35006684]
 [ 4.47412685]
 [-0.94566575]
 [-1.64390542]
 [ 0.38489983]
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 [ 4.29416631]
 [-1.90266621]]
[[ -1.80968195e-02  -3.03005418e-01   2.68131349e-01 ...,  -2.31367691e-01
   -3.40391829e-01   2.76107875e-01]
 [  5.85386852e-02   1.46479361e-01   1.89338938e-03 ...,  -2.22002131e-01
    1.59532769e+00   1.14233726e-01]
 [ -6.14386682e-02   2.57400202e-01   4.68537925e-01 ...,   2.34245512e-01
   -3.10603940e-01   9.64334673e-01]
 ..., 
 [ -1.84526936e-01  -2.39856143e-01  -3.80734982e-01 ...,   9.00137292e-02
   -5.97686818e-01  -3.20532975e-01]
 [ -2.75674739e-01  -1.84902567e-01  -1.83998470e-01 ...,  -1.18524768e-01
   -1.58766302e-01  -3.44310466e-01]
 [  3.94297903e-02   8.67675391e-02  -4.19182329e-02 ...,   5.42235283e-02
    2.89472830e+00  -6.46592884e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16346959]
 [-0.94575102]
 [-1.18980337]
 [-0.76946853]
 [-0.05667528]
 [ 2.61213231]
 [-0.04986175]
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 [ 1.01608812]
 [-0.09110475]
 [ 0.14379538]
 [-0.10446281]
 [-0.99280059]
 [-0.29232321]
 [ 0.87060832]
 [-0.83384657]
 [-0.79152044]
 [-0.61489575]
 [ 0.14105364]
 [-0.35215859]
 [ 4.47271494]
 [-0.94723577]
 [-1.64726311]
 [ 0.38381542]
 [-0.30638661]
 [ 4.29041932]
 [-1.90346088]]
[[ -1.80074711e-02  -3.02468566e-01   2.68552671e-01 ...,  -2.31206469e-01
   -3.42367204e-01   2.76664456e-01]
 [  5.84835985e-02   1.46170677e-01   1.53956787e-03 ...,  -2.22103014e-01
    1.59630481e+00   1.13727504e-01]
 [ -6.15791983e-02   2.56539699e-01   4.68281924e-01 ...,   2.33987780e-01
   -3.11400809e-01   9.64386735e-01]
 ..., 
 [ -1.84431028e-01  -2.39292210e-01  -3.80178197e-01 ...,   9.01967849e-02
   -5.98353662e-01  -3.19873054e-01]
 [ -2.75592826e-01  -1.84418752e-01  -1.83563792e-01 ...,  -1.18369948e-01
   -1.60107669e-01  -3.43593025e-01]
 [  3.93187310e-02   8.61144030e-02  -4.24924897e-02 ...,   5.40289257e-02
    2.89504969e+00  -6.61177385e-02]]
Progress: 78.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16080512]
 [-0.94378866]
 [-1.18903806]
 [-0.76719449]
 [-0.05513304]
 [ 2.61366916]
 [-0.04754463]
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 [ 1.01678416]
 [-0.08995518]
 [ 0.14555995]
 [-0.10251653]
 [-0.99176812]
 [-0.29001294]
 [ 0.87268977]
 [-0.83215939]
 [-0.79088774]
 [-0.61332624]
 [ 0.14275525]
 [-0.35007508]
 [ 4.47333278]
 [-0.94564694]
 [-1.64568443]
 [ 0.38547528]
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 [ 4.29451791]
 [-1.90217155]]
[[ -1.80753746e-02  -3.02823515e-01   2.68169814e-01 ...,  -2.31322712e-01
   -3.42451825e-01   2.76111961e-01]
 [  5.84693272e-02   1.46093433e-01   1.51245321e-03 ...,  -2.22128409e-01
    1.59637566e+00   1.13680616e-01]
 [ -6.16678119e-02   2.56124480e-01   4.67597953e-01 ...,   2.33839399e-01
   -3.11232145e-01   9.63497700e-01]
 ..., 
 [ -1.84481536e-01  -2.39597115e-01  -3.80526620e-01 ...,   9.01029949e-02
   -5.97629758e-01  -3.20465916e-01]
 [ -2.75601839e-01  -1.84478106e-01  -1.83696328e-01 ...,  -1.18388151e-01
   -1.59653560e-01  -3.43795361e-01]
 [  3.92667120e-02   8.57832950e-02  -4.29230851e-02 ...,   5.39237021e-02
    2.89531075e+00  -6.68565044e-02]]
Progress: 78.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16100593]
 [-0.94284152]
 [-1.18728166]
 [-0.76763202]
 [-0.05520081]
 [ 2.61435848]
 [-0.04718024]
 [-1.09279755]
 [-0.52194328]
 [ 1.01806932]
 [-0.09052454]
 [ 0.14562559]
 [-0.10150994]
 [-0.99047241]
 [-0.28977632]
 [ 0.87280186]
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 [-0.78969688]
 [-0.61306012]
 [ 0.14330348]
 [-0.35011667]
 [ 4.47375369]
 [-0.94524072]
 [-1.64653856]
 [ 0.38569602]
 [-0.30345886]
 [ 4.29481696]
 [-1.90163689]]
[[ -1.80929775e-02  -3.02884290e-01   2.68081851e-01 ...,  -2.31339566e-01
   -3.40980125e-01   2.75961050e-01]
 [  5.84725525e-02   1.46111912e-01   1.52327631e-03 ...,  -2.22122182e-01
    1.59637359e+00   1.13695651e-01]
 [ -6.19024484e-02   2.54796729e-01   4.65999902e-01 ...,   2.33404815e-01
   -3.07774040e-01   9.61760302e-01]
 ..., 
 [ -1.84421620e-01  -2.39242960e-01  -3.80195459e-01 ...,   9.02195568e-02
   -5.98093098e-01  -3.20354620e-01]
 [ -2.75635217e-01  -1.84657771e-01  -1.83981699e-01 ...,  -1.18447640e-01
   -1.58754611e-01  -3.44131709e-01]
 [  3.93250215e-02   8.61256511e-02  -4.24934074e-02 ...,   5.40337091e-02
    2.89520505e+00  -6.62536377e-02]]
Progress: 78.6% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16249157]
 [-0.9447556 ]
 [-1.1879994 ]
 [-0.76954446]
 [-0.05635962]
 [ 2.61245488]
 [-0.04896995]
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 [ 1.01683869]
 [-0.09165607]
 [ 0.1445716 ]
 [-0.1036989 ]
 [-0.99220379]
 [-0.29122415]
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 [-0.79052493]
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 [ 4.47419418]
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 [ 4.29249484]
 [-1.90324733]]
[[ -1.81861360e-02  -3.03400324e-01   2.67660003e-01 ...,  -2.31507676e-01
   -3.39502579e-01   2.75285469e-01]
 [  5.84311849e-02   1.45867342e-01   1.22074574e-03 ...,  -2.22200018e-01
    1.59737120e+00   1.13181557e-01]
 [ -6.17247194e-02   2.55741562e-01   4.67526326e-01 ...,   2.33732220e-01
   -3.09578631e-01   9.64011176e-01]
 ..., 
 [ -1.84351736e-01  -2.38858657e-01  -3.79834526e-01 ...,   9.03459672e-02
   -5.99956592e-01  -3.19844108e-01]
 [ -2.75620081e-01  -1.84590033e-01  -1.83880309e-01 ...,  -1.18421259e-01
   -1.58643175e-01  -3.43985673e-01]
 [  3.93556272e-02   8.62713409e-02  -4.22714468e-02 ...,   5.40869511e-02
    2.89509782e+00  -6.56649581e-02]]
Progress: 78.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16434111]
 [-0.94715374]
 [-1.19029543]
 [-0.77261818]
 [-0.05962859]
 [ 2.61232598]
 [-0.05122428]
 [-1.09584825]
 [-0.52629954]
 [ 1.01520962]
 [-0.09390704]
 [ 0.14253549]
 [-0.10609191]
 [-0.99383335]
 [-0.29372024]
 [ 0.86922101]
 [-0.83531821]
 [-0.79138506]
 [-0.61634567]
 [ 0.13990658]
 [-0.35250111]
 [ 4.47311143]
 [-0.94837686]
 [-1.64853299]
 [ 0.38329747]
 [-0.30837353]
 [ 4.28951244]
 [-1.90440736]]
[[ -1.81323259e-02  -3.03031394e-01   2.68193702e-01 ...,  -2.31417134e-01
   -3.42203598e-01   2.75855712e-01]
 [  5.84268956e-02   1.45842375e-01   1.29398039e-03 ...,  -2.22209757e-01
    1.59731875e+00   1.13180101e-01]
 [ -6.16262795e-02   2.56340156e-01   4.68465162e-01 ...,   2.33888986e-01
   -3.12168446e-01   9.65748557e-01]
 ..., 
 [ -1.84260666e-01  -2.38316910e-01  -3.79522000e-01 ...,   9.05202838e-02
   -6.01708163e-01  -3.19185842e-01]
 [ -2.75484981e-01  -1.83807974e-01  -1.83197776e-01 ...,  -1.18186253e-01
   -1.60414552e-01  -3.42709574e-01]
 [  3.93068877e-02   8.59823631e-02  -4.22772525e-02 ...,   5.39964210e-02
    2.89522181e+00  -6.62819694e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16041177]
 [-0.9440808 ]
 [-1.18907474]
 [-0.76808503]
 [-0.05601004]
 [ 2.61411702]
 [-0.04769379]
 [-1.09215518]
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 [ 1.01688214]
 [-0.09042076]
 [ 0.14554557]
 [-0.10249388]
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 [ 0.87258216]
 [-0.83208301]
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 [ 0.14299517]
 [-0.34967696]
 [ 4.47365902]
 [-0.94408695]
 [-1.64507822]
 [ 0.38575691]
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 [ 4.29503052]
 [-1.90280156]]
[[ -1.81733824e-02  -3.03267599e-01   2.67949743e-01 ...,  -2.31494542e-01
   -3.41673994e-01   2.74869316e-01]
 [  5.83844339e-02   1.45601584e-01   1.12920979e-03 ...,  -2.22282568e-01
    1.59735187e+00   1.13026825e-01]
 [ -6.15696458e-02   2.56698588e-01   4.67896564e-01 ...,   2.33998077e-01
   -3.10103250e-01   9.64113714e-01]
 ..., 
 [ -1.84288114e-01  -2.38465373e-01  -3.79535231e-01 ...,   9.04697455e-02
   -6.00950930e-01  -3.19291072e-01]
 [ -2.75477458e-01  -1.83771893e-01  -1.83243256e-01 ...,  -1.18171639e-01
   -1.60683346e-01  -3.42572117e-01]
 [  3.93034307e-02   8.59686712e-02  -4.23111079e-02 ...,   5.39977253e-02
    2.89518121e+00  -6.61033394e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16015934]
 [-0.94415286]
 [-1.1894716 ]
 [-0.76722252]
 [-0.05519485]
 [ 2.61382964]
 [-0.04736112]
 [-1.09090028]
 [-0.52424   ]
 [ 1.01649153]
 [-0.09024182]
 [ 0.14579414]
 [-0.10215416]
 [-0.99182931]
 [-0.2911638 ]
 [ 0.87305816]
 [-0.83222777]
 [-0.78994908]
 [-0.61488889]
 [ 0.14313202]
 [-0.34960388]
 [ 4.47416249]
 [-0.94326204]
 [-1.64470351]
 [ 0.38578835]
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 [ 4.29463487]
 [-1.90355725]]
[[ -1.81732791e-02  -3.03256005e-01   2.68241661e-01 ...,  -2.31493895e-01
   -3.40277276e-01   2.75058312e-01]
 [  5.84189381e-02   1.45791347e-01   1.35405065e-03 ...,  -2.22221842e-01
    1.59714896e+00   1.13380208e-01]
 [ -6.14662694e-02   2.57321062e-01   4.68282091e-01 ...,   2.34186583e-01
   -3.11565734e-01   9.65369385e-01]
 ..., 
 [ -1.84294393e-01  -2.38483367e-01  -3.79460081e-01 ...,   9.04604474e-02
   -6.00141568e-01  -3.19669128e-01]
 [ -2.75500065e-01  -1.83900930e-01  -1.83350631e-01 ...,  -1.18217679e-01
   -1.59408572e-01  -3.42913928e-01]
 [  3.92877288e-02   8.58642363e-02  -4.23154397e-02 ...,   5.39648276e-02
    2.89509324e+00  -6.58574924e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.164559  ]
 [-0.94812445]
 [-1.19243796]
 [-0.77070521]
 [-0.05870823]
 [ 2.61224247]
 [-0.05108841]
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 [ 1.01344268]
 [-0.09366248]
 [ 0.14252472]
 [-0.10604615]
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 [ 0.86967494]
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 [ 0.1394031 ]
 [-0.35345716]
 [ 4.473125  ]
 [-0.94743169]
 [-1.64860516]
 [ 0.3827809 ]
 [-0.30797008]
 [ 4.2875499 ]
 [-1.9063015 ]]
[[ -1.81312763e-02  -3.03074635e-01   2.68693428e-01 ...,  -2.31431119e-01
   -3.41033037e-01   2.75999928e-01]
 [  5.84617378e-02   1.46048196e-01   1.64036046e-03 ...,  -2.22140497e-01
    1.59667573e+00   1.13877712e-01]
 [ -6.13716046e-02   2.57840269e-01   4.69020695e-01 ...,   2.34366253e-01
   -3.14721405e-01   9.67631738e-01]
 ..., 
 [ -1.84302481e-01  -2.38564768e-01  -3.79638718e-01 ...,   9.04419616e-02
   -5.99474945e-01  -3.19889114e-01]
 [ -2.75372052e-01  -1.83198872e-01  -1.82513962e-01 ...,  -1.17993859e-01
   -1.61971667e-01  -3.41738323e-01]
 [  3.93495534e-02   8.62451645e-02  -4.15770447e-02 ...,   5.40860228e-02
    2.89506247e+00  -6.53630526e-02]]
Progress: 78.7% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16231394]
 [-0.94632552]
 [-1.19049475]
 [-0.76851451]
 [-0.05706   ]
 [ 2.61410305]
 [-0.04962226]
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 [ 1.01332726]
 [-0.09196247]
 [ 0.14423153]
 [-0.10395379]
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 [ 0.87106307]
 [-0.83450569]
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 [ 0.14154647]
 [-0.35200298]
 [ 4.47282147]
 [-0.9453427 ]
 [-1.64720816]
 [ 0.38371133]
 [-0.30587712]
 [ 4.29099838]
 [-1.90432389]]
[[ -1.83221498e-02  -3.04116721e-01   2.67676185e-01 ...,  -2.31776801e-01
   -3.39024666e-01   2.74402898e-01]
 [  5.84975354e-02   1.46262695e-01   1.79998641e-03 ...,  -2.22084199e-01
    1.59650650e+00   1.14109305e-01]
 [ -6.14484242e-02   2.57399297e-01   4.68623032e-01 ...,   2.34217064e-01
   -3.14125455e-01   9.66135151e-01]
 ..., 
 [ -1.84318862e-01  -2.38647545e-01  -3.79797999e-01 ...,   9.04002835e-02
   -5.98556786e-01  -3.20062378e-01]
 [ -2.75269518e-01  -1.82630699e-01  -1.81871365e-01 ...,  -1.17819475e-01
   -1.61816322e-01  -3.41247079e-01]
 [  3.91861072e-02   8.53290140e-02  -4.25778059e-02 ...,   5.37804864e-02
    2.89560816e+00  -6.70336661e-02]]
Progress: 78.7% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16183701]
 [-0.94567186]
 [-1.19014344]
 [-0.76843518]
 [-0.05708613]
 [ 2.61515138]
 [-0.04867834]
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 [ 1.01402172]
 [-0.09130331]
 [ 0.14471633]
 [-0.10274167]
 [-0.99266121]
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 [ 0.87077534]
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 [ 0.14195413]
 [-0.3517371 ]
 [ 4.473244  ]
 [-0.9446814 ]
 [-1.64727898]
 [ 0.3843909 ]
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 [ 4.29262406]
 [-1.9038088 ]]
[[ -1.83046878e-02  -3.04013146e-01   2.67500011e-01 ...,  -2.31749839e-01
   -3.40366616e-01   2.74208558e-01]
 [  5.84651209e-02   1.46080999e-01   1.59777239e-03 ...,  -2.22143774e-01
    1.59648057e+00   1.13974713e-01]
 [ -6.15374417e-02   2.56902263e-01   4.67849697e-01 ...,   2.34062239e-01
   -3.12482243e-01   9.64851030e-01]
 ..., 
 [ -1.84285597e-01  -2.38473338e-01  -3.79717421e-01 ...,   9.04630083e-02
   -5.99513478e-01  -3.19929313e-01]
 [ -2.75321950e-01  -1.82925743e-01  -1.82182047e-01 ...,  -1.17916272e-01
   -1.61448749e-01  -3.41634445e-01]
 [  3.90944778e-02   8.48288263e-02  -4.30266110e-02 ...,   5.36123314e-02
    2.89587019e+00  -6.78484452e-02]]
Progress: 78.7% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16435553]
 [-0.9473344 ]
 [-1.19319173]
 [-0.76966396]
 [-0.05790361]
 [ 2.61443403]
 [-0.05091325]
 [-1.09333469]
 [-0.52911933]
 [ 1.01052945]
 [-0.09331616]
 [ 0.14300209]
 [-0.10355914]
 [-0.99359672]
 [-0.29492823]
 [ 0.86821681]
 [-0.83600587]
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 [ 0.14076989]
 [-0.35389264]
 [ 4.47377393]
 [-0.94506023]
 [-1.64904219]
 [ 0.38246783]
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 [ 4.28885104]
 [-1.9048145 ]]
[[ -1.85032259e-02  -3.05149948e-01   2.66400316e-01 ...,  -2.32106412e-01
   -3.39401516e-01   2.72322038e-01]
 [  5.85512151e-02   1.46576369e-01   1.88136359e-03 ...,  -2.21969431e-01
    1.59648369e+00   1.14388603e-01]
 [ -6.14021634e-02   2.57635355e-01   4.68862710e-01 ...,   2.34337130e-01
   -3.11593213e-01   9.65711324e-01]
 ..., 
 [ -1.84280247e-01  -2.38439018e-01  -3.79949440e-01 ...,   9.04810200e-02
   -5.99611224e-01  -3.19934546e-01]
 [ -2.75272230e-01  -1.82658403e-01  -1.81640812e-01 ...,  -1.17860113e-01
   -1.61183958e-01  -3.41620685e-01]
 [  3.89874582e-02   8.41992351e-02  -4.33888653e-02 ...,   5.34041819e-02
    2.89591630e+00  -6.86957588e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16087736]
 [-0.9439501 ]
 [-1.18845526]
 [-0.76757965]
 [-0.05560562]
 [ 2.61636007]
 [-0.04812214]
 [-1.09103851]
 [-0.52594453]
 [ 1.01275539]
 [-0.0904344 ]
 [ 0.14622852]
 [-0.10019939]
 [-0.99169835]
 [-0.29111311]
 [ 0.87277383]
 [-0.8319591 ]
 [-0.79120292]
 [-0.61597286]
 [ 0.14382902]
 [-0.35041945]
 [ 4.47428476]
 [-0.94308614]
 [-1.64485541]
 [ 0.38516513]
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 [ 4.29535196]
 [-1.90312061]]
[[ -1.88051587e-02  -3.06866286e-01   2.64401371e-01 ...,  -2.32656737e-01
   -3.36795417e-01   2.69689468e-01]
 [  5.85844693e-02   1.46763999e-01   1.95120076e-03 ...,  -2.21908031e-01
    1.59609357e+00   1.14730191e-01]
 [ -6.14886131e-02   2.57148385e-01   4.68106968e-01 ...,   2.34169488e-01
   -3.11675019e-01   9.64288422e-01]
 ..., 
 [ -1.84197191e-01  -2.37958476e-01  -3.79670414e-01 ...,   9.06277960e-02
   -6.00587716e-01  -3.19300708e-01]
 [ -2.75356225e-01  -1.83093180e-01  -1.82111435e-01 ...,  -1.17988715e-01
   -1.60324627e-01  -3.42321349e-01]
 [  3.89117101e-02   8.37616295e-02  -4.38140722e-02 ...,   5.32602959e-02
    2.89593171e+00  -6.92480556e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16923115]
 [-0.95162561]
 [-1.19272333]
 [-0.77475967]
 [-0.06194167]
 [ 2.60954454]
 [-0.05587245]
 [-1.09618359]
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 [ 1.00929414]
 [-0.09690155]
 [ 0.13931006]
 [-0.10873069]
 [-0.99931891]
 [-0.29844438]
 [ 0.86530269]
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 [-0.79670733]
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 [ 0.13673349]
 [-0.3573028 ]
 [ 4.47237922]
 [-0.95157696]
 [-1.6507968 ]
 [ 0.37819733]
 [-0.3105056 ]
 [ 4.28256505]
 [-1.90790827]]
[[ -1.84118197e-02  -3.04651596e-01   2.66392342e-01 ...,  -2.31961193e-01
   -3.40653034e-01   2.73072578e-01]
 [  5.85692827e-02   1.46674333e-01   1.89256867e-03 ...,  -2.21936779e-01
    1.59606333e+00   1.14586092e-01]
 [ -6.11669846e-02   2.59130763e-01   4.70059020e-01 ...,   2.34818797e-01
   -3.15885955e-01   9.69054486e-01]
 ..., 
 [ -1.84175321e-01  -2.37836677e-01  -3.79513297e-01 ...,   9.06712583e-02
   -6.01216472e-01  -3.19049195e-01]
 [ -2.75293067e-01  -1.82737416e-01  -1.81701410e-01 ...,  -1.17877727e-01
   -1.61482473e-01  -3.41849170e-01]
 [  3.90432909e-02   8.44671909e-02  -4.32546807e-02 ...,   5.34830805e-02
    2.89592306e+00  -6.83951348e-02]]
Progress: 78.7% ... Training loss: 0.069 ... Validation loss: 0.141[[-0.15826804]
 [-0.94194387]
 [-1.18472966]
 [-0.76462822]
 [-0.05246763]
 [ 2.61463824]
 [-0.04627801]
 [-1.08803958]
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 [ 1.01738479]
 [-0.08703673]
 [ 0.14891779]
 [-0.09794216]
 [-0.99152234]
 [-0.28860004]
 [ 0.87631017]
 [-0.82852171]
 [-0.78740213]
 [-0.61236591]
 [ 0.14589162]
 [-0.34781783]
 [ 4.47452624]
 [-0.94190539]
 [-1.641496  ]
 [ 0.38640255]
 [-0.3014391 ]
 [ 4.29929228]
 [-1.90315987]]
[[ -1.86273739e-02  -3.05763621e-01   2.65347038e-01 ...,  -2.32325713e-01
   -3.36622542e-01   2.71439478e-01]
 [  5.85688872e-02   1.46672284e-01   1.89232245e-03 ...,  -2.21937411e-01
    1.59605537e+00   1.14594006e-01]
 [ -6.14075789e-02   2.57791515e-01   4.67812992e-01 ...,   2.34366412e-01
   -3.05640621e-01   9.64246531e-01]
 ..., 
 [ -1.84321614e-01  -2.38602701e-01  -3.80294995e-01 ...,   9.04134409e-02
   -5.98574995e-01  -3.20243819e-01]
 [ -2.75464199e-01  -1.83664438e-01  -1.82653227e-01 ...,  -1.18165873e-01
   -1.58371131e-01  -3.43194046e-01]
 [  3.89669015e-02   8.40423938e-02  -4.36529899e-02 ...,   5.33509523e-02
    2.89597555e+00  -6.84748953e-02]]
Progress: 78.7% ... Training loss: 0.065 ... Validation loss: 0.143[[-0.16538995]
 [-0.94778116]
 [-1.18938731]
 [-0.77118827]
 [-0.05780627]
 [ 2.61162264]
 [-0.05241665]
 [-1.09368357]
 [-0.52772199]
 [ 1.01423382]
 [-0.09378976]
 [ 0.14309412]
 [-0.10410321]
 [-0.99650164]
 [-0.29451336]
 [ 0.86984359]
 [-0.83509088]
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 [-0.61735773]
 [ 0.1404297 ]
 [-0.35307078]
 [ 4.47307428]
 [-0.94819788]
 [-1.64828733]
 [ 0.38148957]
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 [ 4.28797118]
 [-1.90706572]]
[[ -1.82855048e-02  -3.03781986e-01   2.67093405e-01 ...,  -2.31693033e-01
   -3.40289529e-01   2.74469650e-01]
 [  5.86216451e-02   1.46969465e-01   2.08508329e-03 ...,  -2.21840058e-01
    1.59546719e+00   1.15105705e-01]
 [ -6.13464676e-02   2.58093555e-01   4.68596231e-01 ...,   2.34451172e-01
   -3.07655378e-01   9.66480816e-01]
 ..., 
 [ -1.84217279e-01  -2.38000997e-01  -3.79687368e-01 ...,   9.06056010e-02
   -5.99857458e-01  -3.19126050e-01]
 [ -2.75432972e-01  -1.83500754e-01  -1.82543778e-01 ...,  -1.18107229e-01
   -1.58161377e-01  -3.42999035e-01]
 [  3.90526008e-02   8.45400736e-02  -4.33852871e-02 ...,   5.35058251e-02
    2.89595834e+00  -6.77930584e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.1622233 ]
 [-0.94501744]
 [-1.18643941]
 [-0.76888057]
 [-0.05581667]
 [ 2.61375529]
 [-0.04971028]
 [-1.09239551]
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 [ 1.01624765]
 [-0.09137633]
 [ 0.14549775]
 [-0.10140862]
 [-0.99422877]
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 [ 0.87312115]
 [-0.8323844 ]
 [-0.78991911]
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 [ 0.14322681]
 [-0.35040119]
 [ 4.47435184]
 [-0.94614527]
 [-1.64618459]
 [ 0.38426404]
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 [ 4.29309941]
 [-1.90518135]]
[[ -1.84836346e-02  -3.04903082e-01   2.65980960e-01 ...,  -2.32063581e-01
   -3.38832392e-01   2.72276464e-01]
 [  5.86362095e-02   1.47051791e-01   2.12161283e-03 ...,  -2.21811491e-01
    1.59534501e+00   1.15080641e-01]
 [ -6.15157661e-02   2.57100294e-01   4.67438776e-01 ...,   2.34097889e-01
   -3.06692557e-01   9.64964065e-01]
 ..., 
 [ -1.84285502e-01  -2.38352049e-01  -3.80066068e-01 ...,   9.04810714e-02
   -5.98888713e-01  -3.19651267e-01]
 [ -2.75475205e-01  -1.83771286e-01  -1.82837530e-01 ...,  -1.18196370e-01
   -1.58468850e-01  -3.43359690e-01]
 [  3.90806275e-02   8.46993264e-02  -4.29338062e-02 ...,   5.35666841e-02
    2.89582940e+00  -6.77241315e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16442238]
 [-0.94712981]
 [-1.18877713]
 [-0.7702339 ]
 [-0.05782395]
 [ 2.6123882 ]
 [-0.05147218]
 [-1.09315471]
 [-0.52725012]
 [ 1.0137721 ]
 [-0.093599  ]
 [ 0.14336551]
 [-0.10391952]
 [-0.99623458]
 [-0.29402796]
 [ 0.8704972 ]
 [-0.83483709]
 [-0.79244784]
 [-0.61672177]
 [ 0.1409023 ]
 [-0.35263965]
 [ 4.47355756]
 [-0.94725959]
 [-1.64723355]
 [ 0.38248264]
 [-0.30614098]
 [ 4.28969039]
 [-1.90674939]]
[[ -1.84085957e-02  -3.04482340e-01   2.66901126e-01 ...,  -2.31939624e-01
   -3.39573959e-01   2.72781905e-01]
 [  5.86278235e-02   1.47003369e-01   2.08465905e-03 ...,  -2.21826009e-01
    1.59535609e+00   1.15024669e-01]
 [ -6.13304255e-02   2.58116754e-01   4.68506850e-01 ...,   2.34433872e-01
   -3.10898730e-01   9.66835920e-01]
 ..., 
 [ -1.84211319e-01  -2.37919825e-01  -3.79717350e-01 ...,   9.06176552e-02
   -6.00537210e-01  -3.18979653e-01]
 [ -2.75447572e-01  -1.83609424e-01  -1.82420092e-01 ...,  -1.18158738e-01
   -1.57842879e-01  -3.43272355e-01]
 [  3.90847317e-02   8.47171304e-02  -4.28670352e-02 ...,   5.35729959e-02
    2.89572697e+00  -6.76228435e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16112735]
 [-0.94387843]
 [-1.18685521]
 [-0.76665865]
 [-0.05430958]
 [ 2.61577284]
 [-0.04761999]
 [-1.09059185]
 [-0.52402198]
 [ 1.01555041]
 [-0.09091113]
 [ 0.1465378 ]
 [-0.09941032]
 [-0.99293605]
 [-0.29080704]
 [ 0.8745852 ]
 [-0.83163172]
 [-0.79043427]
 [-0.61437898]
 [ 0.14408272]
 [-0.34955478]
 [ 4.47439648]
 [-0.94450076]
 [-1.64553569]
 [ 0.3858935 ]
 [-0.3025504 ]
 [ 4.29480611]
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[[ -1.85762898e-02  -3.05428606e-01   2.66032674e-01 ...,  -2.32263079e-01
   -3.37359257e-01   2.71759819e-01]
 [  5.86318125e-02   1.47025947e-01   2.15576130e-03 ...,  -2.21819477e-01
    1.59531907e+00   1.15180591e-01]
 [ -6.14897420e-02   2.57148983e-01   4.67220154e-01 ...,   2.34132421e-01
   -3.07925501e-01   9.64415588e-01]
 ..., 
 [ -1.84255058e-01  -2.38162560e-01  -3.80160339e-01 ...,   9.05373959e-02
   -5.99291387e-01  -3.19338058e-01]
 [ -2.75446211e-01  -1.83616224e-01  -1.82491387e-01 ...,  -1.18176850e-01
   -1.56642790e-01  -3.43594586e-01]
 [  3.90551460e-02   8.45613980e-02  -4.29190677e-02 ...,   5.35180594e-02
    2.89583303e+00  -6.83614159e-02]]
Progress: 78.7% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16419402]
 [-0.94720048]
 [-1.18875269]
 [-0.77063907]
 [-0.05723138]
 [ 2.61274315]
 [-0.05089003]
 [-1.09296438]
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 [ 1.01541614]
 [-0.09341767]
 [ 0.14341247]
 [-0.10335592]
 [-0.99653307]
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 [ 0.87185672]
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 [ 0.14013841]
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 [ 4.47396125]
 [-0.94852259]
 [-1.64782398]
 [ 0.38310578]
 [-0.30605558]
 [ 4.28954264]
 [-1.90673706]]
[[ -1.82961055e-02  -3.03817746e-01   2.67552423e-01 ...,  -2.31759810e-01
   -3.40673523e-01   2.73462357e-01]
 [  5.85627293e-02   1.46626461e-01   1.98746702e-03 ...,  -2.21933901e-01
    1.59523180e+00   1.14771573e-01]
 [ -6.13292614e-02   2.58094233e-01   4.68356056e-01 ...,   2.34392840e-01
   -3.10971654e-01   9.66954423e-01]
 ..., 
 [ -1.84238882e-01  -2.38069020e-01  -3.80120971e-01 ...,   9.05690078e-02
   -5.99712185e-01  -3.19304368e-01]
 [ -2.75428352e-01  -1.83523982e-01  -1.82387213e-01 ...,  -1.18132714e-01
   -1.57953109e-01  -3.43263823e-01]
 [  3.91654517e-02   8.52173310e-02  -4.22601845e-02 ...,   5.37088034e-02
    2.89582724e+00  -6.79255443e-02]]
Progress: 78.7% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16225074]
 [-0.94448964]
 [-1.18713974]
 [-0.76844072]
 [-0.05507437]
 [ 2.61426793]
 [-0.04833808]
 [-1.09123974]
 [-0.52456189]
 [ 1.0173496 ]
 [-0.09109355]
 [ 0.1456577 ]
 [-0.10099378]
 [-0.99466668]
 [-0.29177649]
 [ 0.87423863]
 [-0.8328775 ]
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 [-0.61412943]
 [ 0.14189762]
 [-0.35079663]
 [ 4.47449409]
 [-0.94685642]
 [-1.64703586]
 [ 0.38497068]
 [-0.30360023]
 [ 4.29313193]
 [-1.90572172]]
[[ -1.82508036e-02  -3.03582249e-01   2.67873893e-01 ...,  -2.31691195e-01
   -3.41049255e-01   2.74035983e-01]
 [  5.84996881e-02   1.46265388e-01   1.59578552e-03 ...,  -2.22053928e-01
    1.59561073e+00   1.14379009e-01]
 [ -6.14844428e-02   2.57150453e-01   4.66919007e-01 ...,   2.34101512e-01
   -3.10408829e-01   9.65210486e-01]
 ..., 
 [ -1.84301495e-01  -2.38424294e-01  -3.80433076e-01 ...,   9.04531981e-02
   -5.98377558e-01  -3.19659924e-01]
 [ -2.75470078e-01  -1.83742729e-01  -1.82587157e-01 ...,  -1.18208954e-01
   -1.57702179e-01  -3.43638963e-01]
 [  3.91786176e-02   8.52837436e-02  -4.21406495e-02 ...,   5.37284749e-02
    2.89593004e+00  -6.78279873e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16378502]
 [-0.94573478]
 [-1.18863711]
 [-0.77023886]
 [-0.05722473]
 [ 2.61425876]
 [-0.04950628]
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 [ 1.01683205]
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 [ 0.14411831]
 [-0.10255196]
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 [-0.29353914]
 [ 0.87175858]
 [-0.83461827]
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 [ 0.14015486]
 [-0.35175227]
 [ 4.47401576]
 [-0.9471966 ]
 [-1.64965323]
 [ 0.38422779]
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 [ 4.29024915]
 [-1.90627435]]
[[ -1.81090373e-02  -3.02807321e-01   2.68514220e-01 ...,  -2.31434608e-01
   -3.41693052e-01   2.74893207e-01]
 [  5.84750608e-02   1.46121110e-01   1.55603354e-03 ...,  -2.22088753e-01
    1.59564742e+00   1.14220027e-01]
 [ -6.16299703e-02   2.56395751e-01   4.66186947e-01 ...,   2.33837081e-01
   -3.09017375e-01   9.65159978e-01]
 ..., 
 [ -1.84376650e-01  -2.38837056e-01  -3.80825458e-01 ...,   9.03159906e-02
   -5.97072209e-01  -3.20043288e-01]
 [ -2.75525012e-01  -1.84091735e-01  -1.82783524e-01 ...,  -1.18295047e-01
   -1.56685608e-01  -3.44023669e-01]
 [  3.92697127e-02   8.58301358e-02  -4.16809723e-02 ...,   5.38946348e-02
    2.89578994e+00  -6.72784240e-02]]
Progress: 78.8% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16169002]
 [-0.94505435]
 [-1.18782062]
 [-0.7680824 ]
 [-0.0551823 ]
 [ 2.61336355]
 [-0.04819966]
 [-1.09080787]
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 [ 1.01893924]
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 [ 0.14645636]
 [-0.10071742]
 [-0.99356552]
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 [ 0.87460199]
 [-0.83354162]
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 [ 0.1421337 ]
 [-0.34916141]
 [ 4.47452788]
 [-0.94505405]
 [-1.64653717]
 [ 0.38557687]
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 [ 4.29324231]
 [-1.90652102]]
[[ -1.82298709e-02  -3.03461839e-01   2.68179149e-01 ...,  -2.31637456e-01
   -3.39484838e-01   2.73685544e-01]
 [  5.84389135e-02   1.45957570e-01   1.32996561e-03 ...,  -2.22143274e-01
    1.59623491e+00   1.14052685e-01]
 [ -6.13993811e-02   2.57463957e-01   4.67305074e-01 ...,   2.34230557e-01
   -3.09080885e-01   9.67247343e-01]
 ..., 
 [ -1.84457035e-01  -2.39295133e-01  -3.81207685e-01 ...,   9.01722681e-02
   -5.95766333e-01  -3.20789400e-01]
 [ -2.75539488e-01  -1.84165203e-01  -1.82750378e-01 ...,  -1.18312315e-01
   -1.56306970e-01  -3.43897793e-01]
 [  3.93998804e-02   8.65134911e-02  -4.05458836e-02 ...,   5.41277816e-02
    2.89581311e+00  -6.61030780e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16435325]
 [-0.94795496]
 [-1.1908816 ]
 [-0.77032927]
 [-0.05756068]
 [ 2.61190181]
 [-0.05060742]
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 [-0.52666271]
 [ 1.0173394 ]
 [-0.09335556]
 [ 0.14349428]
 [-0.10325139]
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 [ 0.87137407]
 [-0.83633936]
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 [ 0.13935643]
 [-0.35171587]
 [ 4.47409707]
 [-0.94654803]
 [-1.64936308]
 [ 0.3833754 ]
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 [ 4.28828629]
 [-1.90817473]]
[[ -1.80754321e-02  -3.02607061e-01   2.68965239e-01 ...,  -2.31353028e-01
   -3.40231210e-01   2.75426130e-01]
 [  5.84405983e-02   1.45967350e-01   1.33843358e-03 ...,  -2.22140480e-01
    1.59620371e+00   1.14072011e-01]
 [ -6.13519579e-02   2.57761657e-01   4.67720576e-01 ...,   2.34317743e-01
   -3.09019512e-01   9.68494657e-01]
 ..., 
 [ -1.84395475e-01  -2.38949987e-01  -3.80931230e-01 ...,   9.02910003e-02
   -5.96970226e-01  -3.20482342e-01]
 [ -2.75511202e-01  -1.83984091e-01  -1.82617301e-01 ...,  -1.18255757e-01
   -1.56721869e-01  -3.43700275e-01]
 [  3.94388145e-02   8.67343065e-02  -4.03456615e-02 ...,   5.41963760e-02
    2.89568011e+00  -6.56595410e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16294673]
 [-0.94703731]
 [-1.18961505]
 [-0.76899061]
 [-0.0565912 ]
 [ 2.61095362]
 [-0.04977695]
 [-1.0912557 ]
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 [ 1.01875054]
 [-0.09206248]
 [ 0.14455023]
 [-0.10224658]
 [-0.99547692]
 [-0.29436646]
 [ 0.87217567]
 [-0.83428486]
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 [ 0.13999009]
 [-0.35058611]
 [ 4.47423506]
 [-0.9455122 ]
 [-1.64738461]
 [ 0.38345008]
 [-0.30522935]
 [ 4.29081305]
 [-1.90817664]]
[[ -1.79891675e-02  -3.02135162e-01   2.69505535e-01 ...,  -2.31211965e-01
   -3.41373625e-01   2.76361650e-01]
 [  5.84810329e-02   1.46195613e-01   1.60525470e-03 ...,  -2.22068432e-01
    1.59601740e+00   1.14438462e-01]
 [ -6.12446550e-02   2.58332263e-01   4.68300045e-01 ...,   2.34497135e-01
   -3.08799296e-01   9.68668140e-01]
 ..., 
 [ -1.84431719e-01  -2.39130001e-01  -3.81154230e-01 ...,   9.02199050e-02
   -5.96499256e-01  -3.20928738e-01]
 [ -2.75508736e-01  -1.83993726e-01  -1.82623521e-01 ...,  -1.18253140e-01
   -1.56479341e-01  -3.43704163e-01]
 [  3.93513774e-02   8.62351548e-02  -4.09667563e-02 ...,   5.40325725e-02
    2.89572061e+00  -6.60196094e-02]]
Progress: 78.8% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.1594485 ]
 [-0.94417182]
 [-1.18719816]
 [-0.76639868]
 [-0.05457679]
 [ 2.61320319]
 [-0.04684477]
 [-1.08919148]
 [-0.52287165]
 [ 1.0196857 ]
 [-0.0896242 ]
 [ 0.14797955]
 [-0.098098  ]
 [-0.99339995]
 [-0.29103133]
 [ 0.87594804]
 [-0.83057557]
 [-0.78846186]
 [-0.61386046]
 [ 0.14314425]
 [-0.34682872]
 [ 4.47461741]
 [-0.94321009]
 [-1.64414525]
 [ 0.38630814]
 [-0.30229323]
 [ 4.29685511]
 [-1.90668716]]
[[ -1.82443722e-02  -3.03598331e-01   2.67947195e-01 ...,  -2.31671608e-01
   -3.39268411e-01   2.74211850e-01]
 [  5.84295168e-02   1.45905888e-01   1.50361268e-03 ...,  -2.22164060e-01
    1.59548000e+00   1.14103202e-01]
 [ -6.13449976e-02   2.57826408e-01   4.67513873e-01 ...,   2.34307110e-01
   -3.08970591e-01   9.68657625e-01]
 ..., 
 [ -1.84448093e-01  -2.39230672e-01  -3.81302689e-01 ...,   9.01862923e-02
   -5.96102859e-01  -3.20832540e-01]
 [ -2.75567929e-01  -1.84344259e-01  -1.82960364e-01 ...,  -1.18359609e-01
   -1.55902870e-01  -3.44177789e-01]
 [  3.92133677e-02   8.53894511e-02  -4.17194523e-02 ...,   5.37648247e-02
    2.89593980e+00  -6.73800155e-02]]
Progress: 78.8% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16677616]
 [-0.95097672]
 [-1.19401987]
 [-0.77282282]
 [-0.06122469]
 [ 2.60995275]
 [-0.05247048]
 [-1.09499184]
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 [ 1.01461631]
 [-0.09643829]
 [ 0.14131103]
 [-0.10454166]
 [-0.99721191]
 [-0.29880027]
 [ 0.867572  ]
 [-0.83876899]
 [-0.79485965]
 [-0.62058954]
 [ 0.13664367]
 [-0.35295171]
 [ 4.47397782]
 [-0.94752633]
 [-1.65103653]
 [ 0.38109065]
 [-0.30932088]
 [ 4.28481727]
 [-1.90935566]]
[[ -1.80603221e-02  -3.02537718e-01   2.68834324e-01 ...,  -2.31344302e-01
   -3.42124206e-01   2.75560394e-01]
 [  5.84466091e-02   1.46019051e-01   1.58333077e-03 ...,  -2.22133005e-01
    1.59511449e+00   1.14176414e-01]
 [ -6.11727800e-02   2.58901865e-01   4.68503164e-01 ...,   2.34642535e-01
   -3.10100962e-01   9.71294766e-01]
 ..., 
 [ -1.84421545e-01  -2.39091859e-01  -3.81202886e-01 ...,   9.02311840e-02
   -5.97198280e-01  -3.20628810e-01]
 [ -2.75437466e-01  -1.83584541e-01  -1.82089978e-01 ...,  -1.18118928e-01
   -1.57343272e-01  -3.43294702e-01]
 [  3.93574636e-02   8.62318954e-02  -4.09089814e-02 ...,   5.40339288e-02
    2.89580086e+00  -6.63241686e-02]]
Progress: 78.8% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.16222109]
 [-0.94692793]
 [-1.19111852]
 [-0.76833629]
 [-0.05680518]
 [ 2.61298635]
 [-0.04781872]
 [-1.09098414]
 [-0.52621175]
 [ 1.01746502]
 [-0.09219382]
 [ 0.1458156 ]
 [-0.09891161]
 [-0.99310878]
 [-0.29468695]
 [ 0.87297466]
 [-0.83471662]
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 [-0.61755957]
 [ 0.14097601]
 [-0.34854063]
 [ 4.47555727]
 [-0.9428476 ]
 [-1.64661013]
 [ 0.38476124]
 [-0.30505818]
 [ 4.29079354]
 [-1.90732128]]
[[ -1.83690110e-02  -3.04262017e-01   2.67036324e-01 ...,  -2.31914613e-01
   -3.36740941e-01   2.73518977e-01]
 [  5.84285007e-02   1.45918556e-01   1.54855958e-03 ...,  -2.22166100e-01
    1.59516698e+00   1.14081960e-01]
 [ -6.12603181e-02   2.58361705e-01   4.67299383e-01 ...,   2.34471189e-01
   -3.03879931e-01   9.69545010e-01]
 ..., 
 [ -1.84519554e-01  -2.39644307e-01  -3.81862564e-01 ...,   9.00521945e-02
   -5.95033806e-01  -3.21611233e-01]
 [ -2.75592311e-01  -1.84456443e-01  -1.82823235e-01 ...,  -1.18401355e-01
   -1.54954115e-01  -3.44466414e-01]
 [  3.94264178e-02   8.66084289e-02  -4.05360135e-02 ...,   5.41662363e-02
    2.89569890e+00  -6.59257332e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16504598]
 [-0.94968827]
 [-1.19327641]
 [-0.77025939]
 [-0.05853596]
 [ 2.61164676]
 [-0.05011238]
 [-1.09287741]
 [-0.52830596]
 [ 1.01612325]
 [-0.09427014]
 [ 0.14293474]
 [-0.10217248]
 [-0.9946533 ]
 [-0.29751451]
 [ 0.86989891]
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 [-0.79446349]
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 [ 0.13821383]
 [-0.35194776]
 [ 4.47439083]
 [-0.9445419 ]
 [-1.64999227]
 [ 0.38253552]
 [-0.30701619]
 [ 4.28565319]
 [-1.90852259]]
[[ -1.81162834e-02  -3.02815572e-01   2.68644345e-01 ...,  -2.31454606e-01
   -3.37440658e-01   2.75549660e-01]
 [  5.84570910e-02   1.46091771e-01   1.67771289e-03 ...,  -2.22109084e-01
    1.59437392e+00   1.14526923e-01]
 [ -6.12583523e-02   2.58410225e-01   4.67417509e-01 ...,   2.34509387e-01
   -3.04483178e-01   9.69682751e-01]
 ..., 
 [ -1.84509003e-01  -2.39594105e-01  -3.81755008e-01 ...,   9.00756572e-02
   -5.94828120e-01  -3.21409325e-01]
 [ -2.75547801e-01  -1.84220574e-01  -1.82717509e-01 ...,  -1.18333585e-01
   -1.55055703e-01  -3.44454875e-01]
 [  3.94980541e-02   8.70328246e-02  -4.01209091e-02 ...,   5.42930684e-02
    2.89561531e+00  -6.53126249e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.1611527 ]
 [-0.94638555]
 [-1.19122258]
 [-0.76644874]
 [-0.05463597]
 [ 2.61462148]
 [-0.04608069]
 [-1.08985635]
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 [ 1.01837071]
 [-0.09054813]
 [ 0.14681616]
 [-0.09764927]
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 [-0.29387061]
 [ 0.87382288]
 [-0.83386905]
 [-0.79151411]
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 [ 0.14196242]
 [-0.34893231]
 [ 4.47526531]
 [-0.94007361]
 [-1.6472328 ]
 [ 0.38586503]
 [-0.30361787]
 [ 4.29132835]
 [-1.90716897]]
[[ -1.82196286e-02  -3.03300449e-01   2.68406579e-01 ...,  -2.31630096e-01
   -3.33098122e-01   2.75071210e-01]
 [  5.84365520e-02   1.45973128e-01   1.54745707e-03 ...,  -2.22148700e-01
    1.59458502e+00   1.14309339e-01]
 [ -6.12991410e-02   2.58148022e-01   4.66758953e-01 ...,   2.34436951e-01
   -3.03949509e-01   9.68271277e-01]
 ..., 
 [ -1.84570517e-01  -2.39939409e-01  -3.81864614e-01 ...,   8.99667283e-02
   -5.93743032e-01  -3.21733257e-01]
 [ -2.75653943e-01  -1.84800255e-01  -1.83014927e-01 ...,  -1.18528406e-01
   -1.52602719e-01  -3.45291837e-01]
 [  3.94620046e-02   8.68364439e-02  -4.02367583e-02 ...,   5.42392072e-02
    2.89584029e+00  -6.54890001e-02]]
Progress: 78.8% ... Training loss: 0.063 ... Validation loss: 0.145[[-0.16595317]
 [-0.94914394]
 [-1.19232243]
 [-0.77138153]
 [-0.05794702]
 [ 2.61239761]
 [-0.05042563]
 [-1.09265328]
 [-0.52843548]
 [ 1.01657405]
 [-0.09459898]
 [ 0.14385558]
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 [-0.99490646]
 [-0.29654623]
 [ 0.87075573]
 [-0.83737164]
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 [ 0.1383327 ]
 [-0.35193912]
 [ 4.47356911]
 [-0.94533763]
 [-1.65030013]
 [ 0.38288853]
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 [ 4.28492394]
 [-1.91015314]]
[[ -1.81202793e-02  -3.02678823e-01   2.68856456e-01 ...,  -2.31425381e-01
   -3.33913456e-01   2.75598662e-01]
 [  5.84557985e-02   1.46092182e-01   1.69044355e-03 ...,  -2.22110363e-01
    1.59436166e+00   1.14581890e-01]
 [ -6.12386647e-02   2.58548177e-01   4.67684840e-01 ...,   2.34564748e-01
   -3.05955929e-01   9.70128647e-01]
 ..., 
 [ -1.84485326e-01  -2.39446567e-01  -3.81233012e-01 ...,   9.01330550e-02
   -5.95829799e-01  -3.20793987e-01]
 [ -2.75676669e-01  -1.84929257e-01  -1.83192564e-01 ...,  -1.18570550e-01
   -1.52272114e-01  -3.45632865e-01]
 [  3.94586425e-02   8.68082466e-02  -4.01609194e-02 ...,   5.42293699e-02
    2.89576316e+00  -6.53033611e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16259397]
 [-0.94765575]
 [-1.19032902]
 [-0.76920682]
 [-0.05592472]
 [ 2.61387437]
 [-0.04833218]
 [-1.09006783]
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 [ 1.01784588]
 [-0.09259372]
 [ 0.14638955]
 [-0.0986327 ]
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 [ 0.8749185 ]
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 [ 0.14089512]
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 [ 4.47412656]
 [-0.94354553]
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 [ 0.38451657]
 [-0.30426836]
 [ 4.28969198]
 [-1.90971498]]
[[ -1.83681304e-02  -3.04057150e-01   2.67683748e-01 ...,  -2.31881844e-01
   -3.31072733e-01   2.73396967e-01]
 [  5.85327195e-02   1.46446056e-01   1.92808222e-03 ...,  -2.21981955e-01
    1.59437234e+00   1.15141712e-01]
 [ -6.10947440e-02   2.59217160e-01   4.68523933e-01 ...,   2.34860086e-01
   -3.05453882e-01   9.71186784e-01]
 ..., 
 [ -1.84479913e-01  -2.39454803e-01  -3.81319737e-01 ...,   9.01320475e-02
   -5.94851418e-01  -3.20824706e-01]
 [ -2.75640131e-01  -1.84716067e-01  -1.83092962e-01 ...,  -1.18505881e-01
   -1.52456634e-01  -3.45520982e-01]
 [  3.92637228e-02   8.57507792e-02  -4.10052473e-02 ...,   5.38736241e-02
    2.89630582e+00  -6.69398483e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16488388]
 [-0.94991915]
 [-1.19191572]
 [-0.77164864]
 [-0.05890098]
 [ 2.61263119]
 [-0.05027951]
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 [ 1.01643036]
 [-0.09519915]
 [ 0.14421197]
 [-0.1011635 ]
 [-0.99548787]
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 [ 0.87181159]
 [-0.83698111]
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 [ 0.1384018 ]
 [-0.35087099]
 [ 4.47329189]
 [-0.94515448]
 [-1.64835871]
 [ 0.38295303]
 [-0.30691704]
 [ 4.28655821]
 [-1.91033893]]
[[ -1.83017145e-02  -3.03687827e-01   2.68121548e-01 ...,  -2.31756338e-01
   -3.33044960e-01   2.73939558e-01]
 [  5.85088094e-02   1.46310448e-01   1.74167004e-03 ...,  -2.22025652e-01
    1.59480465e+00   1.14819411e-01]
 [ -6.10508344e-02   2.59475078e-01   4.69108978e-01 ...,   2.34949375e-01
   -3.08065160e-01   9.72002546e-01]
 ..., 
 [ -1.84439370e-01  -2.39214000e-01  -3.81094913e-01 ...,   9.02127675e-02
   -5.95647713e-01  -3.20345377e-01]
 [ -2.75657381e-01  -1.84835351e-01  -1.83198230e-01 ...,  -1.18533387e-01
   -1.52381755e-01  -3.45642425e-01]
 [  3.92418593e-02   8.56213378e-02  -4.12021374e-02 ...,   5.38329585e-02
    2.89633515e+00  -6.72153382e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16411713]
 [-0.94969457]
 [-1.19320918]
 [-0.7702852 ]
 [-0.05869823]
 [ 2.61149347]
 [-0.05035408]
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 [ 1.01552932]
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 [ 0.14426615]
 [-0.10147996]
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 [-0.29664993]
 [ 0.87100365]
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 [ 0.13918449]
 [-0.35047106]
 [ 4.47283227]
 [-0.94411786]
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 [ 0.38217594]
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 [ 4.28679618]
 [-1.9107959 ]]
[[ -1.83297409e-02  -3.03863925e-01   2.68437234e-01 ...,  -2.31801626e-01
   -3.31961935e-01   2.73816330e-01]
 [  5.85454426e-02   1.46515759e-01   1.81322339e-03 ...,  -2.21957584e-01
    1.59431449e+00   1.15221234e-01]
 [ -6.08072277e-02   2.60888877e-01   4.70441054e-01 ...,   2.35401204e-01
   -3.08200749e-01   9.73697871e-01]
 ..., 
 [ -1.84526217e-01  -2.39726056e-01  -3.81659728e-01 ...,   9.00552438e-02
   -5.93913775e-01  -3.21185850e-01]
 [ -2.75449458e-01  -1.83687995e-01  -1.81911799e-01 ...,  -1.18163388e-01
   -1.52850890e-01  -3.43760414e-01]
 [  3.91728785e-02   8.52165631e-02  -4.14267735e-02 ...,   5.37025318e-02
    2.89629470e+00  -6.72907149e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16278339]
 [-0.94809734]
 [-1.19289108]
 [-0.7683706 ]
 [-0.05733082]
 [ 2.61103302]
 [-0.04925262]
 [-1.08872235]
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 [ 1.01641408]
 [-0.09367003]
 [ 0.14561972]
 [-0.09942536]
 [-0.99544696]
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 [ 0.87190547]
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 [ 0.14063083]
 [-0.34892076]
 [ 4.47363304]
 [-0.94173298]
 [-1.64463754]
 [ 0.38277001]
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 [ 4.28931769]
 [-1.91006306]]
[[ -1.83854769e-02  -3.04142838e-01   2.68329388e-01 ...,  -2.31881525e-01
   -3.30207629e-01   2.73442100e-01]
 [  5.85459766e-02   1.46511847e-01   1.81418904e-03 ...,  -2.21956848e-01
    1.59425320e+00   1.15186289e-01]
 [ -6.06813658e-02   2.61648567e-01   4.70804011e-01 ...,   2.35646374e-01
   -3.09264456e-01   9.73972789e-01]
 ..., 
 [ -1.84605478e-01  -2.40187995e-01  -3.82131393e-01 ...,   8.99153184e-02
   -5.93145677e-01  -3.21860388e-01]
 [ -2.75409700e-01  -1.83476108e-01  -1.81516337e-01 ...,  -1.18086271e-01
   -1.53680284e-01  -3.43482174e-01]
 [  3.91277376e-02   8.49803733e-02  -4.16087335e-02 ...,   5.36137726e-02
    2.89629239e+00  -6.75306125e-02]]
Progress: 78.8% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.15923893]
 [-0.94588697]
 [-1.19053803]
 [-0.76574064]
 [-0.05504305]
 [ 2.61267561]
 [-0.04678499]
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 [ 1.01748773]
 [-0.09107747]
 [ 0.14790933]
 [-0.09696546]
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 [ 0.87465539]
 [-0.83315465]
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 [ 0.14334435]
 [-0.34687329]
 [ 4.47369885]
 [-0.93939977]
 [-1.64165385]
 [ 0.38502236]
 [-0.30371911]
 [ 4.2948629 ]
 [-1.90809651]]
[[ -1.86209892e-02  -3.05435195e-01   2.67113473e-01 ...,  -2.32286067e-01
   -3.29445384e-01   2.71259059e-01]
 [  5.85224252e-02   1.46406655e-01   1.85087718e-03 ...,  -2.21991146e-01
    1.59351991e+00   1.15262490e-01]
 [ -6.06659700e-02   2.61635070e-01   4.70752294e-01 ...,   2.35680720e-01
   -3.11045070e-01   9.73215178e-01]
 ..., 
 [ -1.84633884e-01  -2.40355052e-01  -3.82290995e-01 ...,   8.98668818e-02
   -5.92555861e-01  -3.22236765e-01]
 [ -2.75399846e-01  -1.83467408e-01  -1.81388930e-01 ...,  -1.18078600e-01
   -1.54870175e-01  -3.43641318e-01]
 [  3.90203545e-02   8.43650146e-02  -4.21905104e-02 ...,   5.34231950e-02
    2.89668805e+00  -6.89097253e-02]]
Progress: 78.9% ... Training loss: 0.063 ... Validation loss: 0.148[[-0.15849842]
 [-0.94470833]
 [-1.1893478 ]
 [-0.76558558]
 [-0.0545436 ]
 [ 2.61311978]
 [-0.04629977]
 [-1.08709592]
 [-0.52428033]
 [ 1.01938871]
 [-0.08956995]
 [ 0.14851351]
 [-0.09715391]
 [-0.99326709]
 [-0.29185723]
 [ 0.87561482]
 [-0.83199847]
 [-0.78970231]
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 [ 0.14360931]
 [-0.34628037]
 [ 4.47436152]
 [-0.93946226]
 [-1.64206653]
 [ 0.38552621]
 [-0.30313538]
 [ 4.29599131]
 [-1.90771756]]
[[ -1.84592706e-02  -3.04557628e-01   2.67955471e-01 ...,  -2.31982340e-01
   -3.30663788e-01   2.72159497e-01]
 [  5.85226636e-02   1.46406895e-01   1.83393401e-03 ...,  -2.21992867e-01
    1.59342037e+00   1.15271811e-01]
 [ -6.07885651e-02   2.61010748e-01   4.70058421e-01 ...,   2.35482674e-01
   -3.08693295e-01   9.71567471e-01]
 ..., 
 [ -1.84598295e-01  -2.40152723e-01  -3.82194723e-01 ...,   8.99350836e-02
   -5.93478072e-01  -3.21978893e-01]
 [ -2.75386249e-01  -1.83419275e-01  -1.81509426e-01 ...,  -1.18058780e-01
   -1.54605837e-01  -3.43770501e-01]
 [  3.90669161e-02   8.46161620e-02  -4.19402735e-02 ...,   5.35125603e-02
    2.89660007e+00  -6.84373746e-02]]
Progress: 78.9% ... Training loss: 0.064 ... Validation loss: 0.149[[-0.16516719]
 [-0.94998458]
 [-1.1938615 ]
 [-0.77106268]
 [-0.06051668]
 [ 2.61245512]
 [-0.05186102]
 [-1.09398656]
 [-0.52979021]
 [ 1.01402161]
 [-0.09531777]
 [ 0.14186096]
 [-0.10438883]
 [-0.99672637]
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 [ 0.86793444]
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 [-0.79602413]
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 [ 0.13753561]
 [-0.35364627]
 [ 4.4725615 ]
 [-0.94467714]
 [-1.65102169]
 [ 0.38105412]
 [-0.30817356]
 [ 4.28586021]
 [-1.9093657 ]]
[[ -1.81717192e-02  -3.02915363e-01   2.69858152e-01 ...,  -2.31428425e-01
   -3.35696556e-01   2.74015525e-01]
 [  5.85854525e-02   1.46757654e-01   2.23690136e-03 ...,  -2.21882013e-01
    1.59324829e+00   1.15707395e-01]
 [ -6.10359292e-02   2.59643896e-01   4.68862847e-01 ...,   2.35034273e-01
   -3.10574618e-01   9.70596856e-01]
 ..., 
 [ -1.84438705e-01  -2.39270575e-01  -3.81306614e-01 ...,   9.02310112e-02
   -5.95616305e-01  -3.20842193e-01]
 [ -2.75247280e-01  -1.82645762e-01  -1.80749246e-01 ...,  -1.17813151e-01
   -1.57276212e-01  -3.42756249e-01]
 [  3.91293635e-02   8.49890235e-02  -4.16578617e-02 ...,   5.36310042e-02
    2.89660244e+00  -6.82517303e-02]]
Progress: 78.9% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.16242717]
 [-0.94853296]
 [-1.19181263]
 [-0.76842062]
 [-0.05880036]
 [ 2.6140141 ]
 [-0.04994256]
 [-1.09177812]
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 [ 1.01530553]
 [-0.09297773]
 [ 0.14400336]
 [-0.10242178]
 [-0.99527946]
 [-0.29593002]
 [ 0.87050756]
 [-0.83538611]
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 [-0.61906434]
 [ 0.13918486]
 [-0.35215613]
 [ 4.47257778]
 [-0.94243337]
 [-1.64864534]
 [ 0.38225071]
 [-0.30599963]
 [ 4.28963721]
 [-1.90824595]]
[[ -1.82993511e-02  -3.03629575e-01   2.69160205e-01 ...,  -2.31657906e-01
   -3.33751943e-01   2.73385522e-01]
 [  5.86012532e-02   1.46839455e-01   2.35498628e-03 ...,  -2.21855046e-01
    1.59313956e+00   1.15881759e-01]
 [ -6.10793762e-02   2.59231324e-01   4.68353062e-01 ...,   2.34967048e-01
   -3.08830214e-01   9.69432002e-01]
 ..., 
 [ -1.84504824e-01  -2.39648610e-01  -3.81774797e-01 ...,   9.01190382e-02
   -5.94798512e-01  -3.21469931e-01]
 [ -2.75262682e-01  -1.82739644e-01  -1.80819453e-01 ...,  -1.17838566e-01
   -1.56484884e-01  -3.42850671e-01]
 [  3.91017993e-02   8.47861875e-02  -4.19201663e-02 ...,   5.35739749e-02
    2.89681929e+00  -6.85270695e-02]]
Progress: 78.9% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16051358]
 [-0.94674717]
 [-1.19041089]
 [-0.76636556]
 [-0.05778069]
 [ 2.61551002]
 [-0.04847078]
 [-1.0907842 ]
 [-0.52640688]
 [ 1.01581895]
 [-0.0922237 ]
 [ 0.14518429]
 [-0.10080525]
 [-0.99385931]
 [-0.29411524]
 [ 0.87206336]
 [-0.83347935]
 [-0.79331358]
 [-0.61814962]
 [ 0.14041222]
 [-0.3505779 ]
 [ 4.47281842]
 [-0.94043619]
 [-1.6470293 ]
 [ 0.38358912]
 [-0.30451631]
 [ 4.2934207 ]
 [-1.90714499]]
[[ -1.83089434e-02  -3.03718867e-01   2.69173114e-01 ...,  -2.31680821e-01
   -3.34692862e-01   2.72906663e-01]
 [  5.86088927e-02   1.46874067e-01   2.31147180e-03 ...,  -2.21842627e-01
    1.59300616e+00   1.15926192e-01]
 [ -6.11581022e-02   2.58782342e-01   4.67989089e-01 ...,   2.34829695e-01
   -3.08671088e-01   9.68294369e-01]
 ..., 
 [ -1.84416966e-01  -2.39179300e-01  -3.81218590e-01 ...,   9.02811017e-02
   -5.97501642e-01  -3.20876004e-01]
 [ -2.75275555e-01  -1.82818857e-01  -1.80873637e-01 ...,  -1.17863752e-01
   -1.56514904e-01  -3.42943203e-01]
 [  3.90560491e-02   8.45104942e-02  -4.19241215e-02 ...,   5.34773778e-02
    2.89689527e+00  -6.89788531e-02]]
Progress: 78.9% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16444524]
 [-0.95040194]
 [-1.19365388]
 [-0.76949741]
 [-0.06084998]
 [ 2.61279197]
 [-0.05248876]
 [-1.09313582]
 [-0.53044082]
 [ 1.01334073]
 [-0.09614362]
 [ 0.14174867]
 [-0.10456104]
 [-0.99681148]
 [-0.29826752]
 [ 0.86786953]
 [-0.83764735]
 [-0.79675971]
 [-0.62152091]
 [ 0.13700259]
 [-0.35405757]
 [ 4.47154355]
 [-0.94307672]
 [-1.64959202]
 [ 0.3802806 ]
 [-0.30821495]
 [ 4.28677617]
 [-1.90948399]]
[[ -1.81625247e-02  -3.02926045e-01   2.70157004e-01 ...,  -2.31413324e-01
   -3.36449702e-01   2.73841944e-01]
 [  5.86064943e-02   1.46859936e-01   2.29449783e-03 ...,  -2.21847169e-01
    1.59302862e+00   1.15901497e-01]
 [ -6.09589658e-02   2.59942702e-01   4.69497486e-01 ...,   2.35190547e-01
   -3.09202600e-01   9.70401687e-01]
 ..., 
 [ -1.84385716e-01  -2.39013613e-01  -3.81102871e-01 ...,   9.03383206e-02
   -5.97758715e-01  -3.20879093e-01]
 [ -2.75219844e-01  -1.82489672e-01  -1.80570664e-01 ...,  -1.17754943e-01
   -1.57010639e-01  -3.42468473e-01]
 [  3.91661431e-02   8.51419990e-02  -4.11374293e-02 ...,   5.36785469e-02
    2.89662068e+00  -6.78303073e-02]]
Progress: 78.9% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.15936522]
 [-0.9453357 ]
 [-1.18986995]
 [-0.76520397]
 [-0.05703806]
 [ 2.61632549]
 [-0.04812697]
 [-1.09021161]
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 [ 1.01514525]
 [-0.09194088]
 [ 0.14602185]
 [-0.09985078]
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 [ 0.87251895]
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 [ 0.14161975]
 [-0.34993264]
 [ 4.47320882]
 [-0.93947543]
 [-1.64571847]
 [ 0.38389385]
 [-0.30432895]
 [ 4.29503588]
 [-1.90647063]]
[[ -1.84279256e-02  -3.04431135e-01   2.68775291e-01 ...,  -2.31890245e-01
   -3.33544221e-01   2.71414888e-01]
 [  5.86093357e-02   1.46874173e-01   2.31400918e-03 ...,  -2.21841776e-01
    1.59296847e+00   1.15946379e-01]
 [ -6.11411329e-02   2.58953396e-01   4.67954147e-01 ...,   2.34861783e-01
   -3.08904120e-01   9.67542807e-01]
 ..., 
 [ -1.84371785e-01  -2.38946881e-01  -3.80906561e-01 ...,   9.03596009e-02
   -5.97993605e-01  -3.20771830e-01]
 [ -2.75238947e-01  -1.82619983e-01  -1.80754204e-01 ...,  -1.17798957e-01
   -1.56891160e-01  -3.42837180e-01]
 [  3.90688519e-02   8.46209574e-02  -4.16866079e-02 ...,   5.35050072e-02
    2.89659963e+00  -6.85762020e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16460987]
 [-0.94976942]
 [-1.19260713]
 [-0.77047704]
 [-0.06129579]
 [ 2.61384013]
 [-0.05296632]
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 [ 1.01139753]
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 [ 0.14130607]
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 [ 0.8678548 ]
 [-0.83776193]
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 [ 0.13705978]
 [-0.35474402]
 [ 4.47173939]
 [-0.94526461]
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 [ 0.38029139]
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 [ 4.28676124]
 [-1.90802108]]
[[ -1.82927212e-02  -3.03606534e-01   2.69210226e-01 ...,  -2.31631369e-01
   -3.36322781e-01   2.72216467e-01]
 [  5.86254207e-02   1.46959331e-01   2.38510942e-03 ...,  -2.21813942e-01
    1.59290873e+00   1.15999574e-01]
 [ -6.12245513e-02   2.58476305e-01   4.67782627e-01 ...,   2.34711075e-01
   -3.09878571e-01   9.67702668e-01]
 ..., 
 [ -1.84286195e-01  -2.38442896e-01  -3.80420880e-01 ...,   9.05219138e-02
   -5.99291426e-01  -3.20372265e-01]
 [ -2.75163455e-01  -1.82182525e-01  -1.80521650e-01 ...,  -1.17658814e-01
   -1.58171769e-01  -3.42446173e-01]
 [  3.90710152e-02   8.46367355e-02  -4.17881047e-02 ...,   5.35097064e-02
    2.89687183e+00  -6.87440627e-02]]
Progress: 78.9% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.15916498]
 [-0.94574667]
 [-1.18729239]
 [-0.76691392]
 [-0.05784328]
 [ 2.61561249]
 [-0.04893512]
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 [ 1.01611747]
 [-0.09183283]
 [ 0.1455253 ]
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 [ 0.14110767]
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 [ 4.47267184]
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 [ 0.3842421 ]
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 [ 4.2954282 ]
 [-1.90527481]]
[[ -1.84030473e-02  -3.04160112e-01   2.68486228e-01 ...,  -2.31797910e-01
   -3.34559627e-01   2.71435398e-01]
 [  5.85510871e-02   1.46545114e-01   1.88131832e-03 ...,  -2.21934496e-01
    1.59416024e+00   1.15140429e-01]
 [ -6.13713642e-02   2.57611117e-01   4.66752735e-01 ...,   2.34436413e-01
   -3.06206355e-01   9.65209635e-01]
 ..., 
 [ -1.84370697e-01  -2.38930203e-01  -3.81033548e-01 ...,   9.03680209e-02
   -5.98011494e-01  -3.21104242e-01]
 [ -2.75220783e-01  -1.82511759e-01  -1.80849512e-01 ...,  -1.17762853e-01
   -1.58195725e-01  -3.42902139e-01]
 [  3.90367460e-02   8.44417783e-02  -4.19504020e-02 ...,   5.34453195e-02
    2.89693989e+00  -6.89551121e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16257927]
 [-0.94878018]
 [-1.18786892]
 [-0.77092517]
 [-0.06117514]
 [ 2.61467066]
 [-0.05194922]
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 [ 1.01487114]
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 [ 0.14302985]
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 [ 0.86972837]
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 [ 0.13860343]
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 [ 4.47236585]
 [-0.94464423]
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 [ 0.38243767]
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 [ 4.29021225]
 [-1.90612847]]
[[ -1.83715372e-02  -3.03948832e-01   2.68481066e-01 ...,  -2.31738878e-01
   -3.33497745e-01   2.71818855e-01]
 [  5.85281685e-02   1.46413594e-01   1.77014135e-03 ...,  -2.21985715e-01
    1.59411476e+00   1.15112186e-01]
 [ -6.14238749e-02   2.57270315e-01   4.66172583e-01 ...,   2.34305636e-01
   -3.07202475e-01   9.65144098e-01]
 ..., 
 [ -1.84363038e-01  -2.38870552e-01  -3.80893452e-01 ...,   9.03771300e-02
   -5.97760490e-01  -3.21256864e-01]
 [ -2.75217720e-01  -1.82501597e-01  -1.81051295e-01 ...,  -1.17758835e-01
   -1.58257286e-01  -3.42630234e-01]
 [  3.90615717e-02   8.46008160e-02  -4.20385926e-02 ...,   5.34915685e-02
    2.89699959e+00  -6.90332964e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16233441]
 [-0.94883056]
 [-1.18841771]
 [-0.76979289]
 [-0.06054471]
 [ 2.61492999]
 [-0.0516514 ]
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 [ 1.01444484]
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 [ 0.14307676]
 [-0.10279804]
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 [ 0.86969848]
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 [ 0.13865068]
 [-0.35212714]
 [ 4.47217448]
 [-0.94383002]
 [-1.64875631]
 [ 0.3822418 ]
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 [ 4.29143404]
 [-1.90640666]]
[[ -1.83127435e-02  -3.03631396e-01   2.68771015e-01 ...,  -2.31648925e-01
   -3.35490807e-01   2.72544265e-01]
 [  5.85690375e-02   1.46648075e-01   2.06856271e-03 ...,  -2.21910925e-01
    1.59378702e+00   1.15541317e-01]
 [ -6.12751091e-02   2.58059751e-01   4.66637119e-01 ...,   2.34565068e-01
   -3.09092872e-01   9.65895065e-01]
 ..., 
 [ -1.84367641e-01  -2.38910671e-01  -3.80943665e-01 ...,   9.03660481e-02
   -5.98211219e-01  -3.21319106e-01]
 [ -2.75249176e-01  -1.82697277e-01  -1.81121637e-01 ...,  -1.17827272e-01
   -1.57378957e-01  -3.42828618e-01]
 [  3.89367756e-02   8.38896228e-02  -4.25918757e-02 ...,   5.32567188e-02
    2.89721163e+00  -7.00297350e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16272939]
 [-0.94912638]
 [-1.18855994]
 [-0.77028609]
 [-0.06023723]
 [ 2.61532431]
 [-0.05129783]
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 [ 1.01442877]
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 [-0.35234763]
 [ 4.472964  ]
 [-0.94426246]
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 [ 0.38262829]
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 [ 4.29055119]
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[[ -1.84400596e-02  -3.04316751e-01   2.68140651e-01 ...,  -2.31868925e-01
   -3.33796420e-01   2.71432573e-01]
 [  5.85339491e-02   1.46447361e-01   1.76365562e-03 ...,  -2.21969572e-01
    1.59421175e+00   1.15252538e-01]
 [ -6.12634939e-02   2.58048704e-01   4.66709435e-01 ...,   2.34566998e-01
   -3.07737700e-01   9.66059238e-01]
 ..., 
 [ -1.84385956e-01  -2.39000493e-01  -3.81226863e-01 ...,   9.03325487e-02
   -5.96511432e-01  -3.21786580e-01]
 [ -2.75205169e-01  -1.82444280e-01  -1.80935589e-01 ...,  -1.17748402e-01
   -1.57908348e-01  -3.42490443e-01]
 [  3.90334928e-02   8.44194182e-02  -4.19281279e-02 ...,   5.34364722e-02
    2.89715212e+00  -6.91358458e-02]]
Progress: 78.9% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16336047]
 [-0.95022685]
 [-1.19045935]
 [-0.76999373]
 [-0.06054813]
 [ 2.61390409]
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 [ 1.01282234]
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 [ 0.14263623]
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 [ 4.47157315]
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 [ 4.28960773]
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[[ -1.83963917e-02  -3.04066232e-01   2.68484829e-01 ...,  -2.31801796e-01
   -3.35093742e-01   2.72190129e-01]
 [  5.85670358e-02   1.46641492e-01   1.97127067e-03 ...,  -2.21907776e-01
    1.59387977e+00   1.15544484e-01]
 [ -6.09306377e-02   2.59946651e-01   4.68785847e-01 ...,   2.35188754e-01
   -3.12582160e-01   9.68997621e-01]
 ..., 
 [ -1.84387946e-01  -2.39004656e-01  -3.81150385e-01 ...,   9.03284720e-02
   -5.96104799e-01  -3.21478666e-01]
 [ -2.75063456e-01  -1.81626334e-01  -1.79958202e-01 ...,  -1.17474065e-01
   -1.58833156e-01  -3.40953213e-01]
 [  3.89407491e-02   8.38648391e-02  -4.27617931e-02 ...,   5.32599994e-02
    2.89740776e+00  -7.03127302e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16064943]
 [-0.94841703]
 [-1.18897063]
 [-0.76741882]
 [-0.05836824]
 [ 2.6145043 ]
 [-0.04959747]
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 [ 1.01541133]
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 [-0.29530355]
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 [-0.83413828]
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 [-0.94297047]
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 [-1.90708977]]
[[ -1.83304677e-02  -3.03662746e-01   2.68521187e-01 ...,  -2.31655009e-01
   -3.34171077e-01   2.72734032e-01]
 [  5.84833695e-02   1.46152559e-01   1.38238631e-03 ...,  -2.22062689e-01
    1.59464638e+00   1.14614496e-01]
 [ -6.08684665e-02   2.60307465e-01   4.68423308e-01 ...,   2.35286638e-01
   -3.09699217e-01   9.67919074e-01]
 ..., 
 [ -1.84500871e-01  -2.39626711e-01  -3.81916481e-01 ...,   9.01269304e-02
   -5.94269131e-01  -3.22379973e-01]
 [ -2.75052211e-01  -1.81592961e-01  -1.80008762e-01 ...,  -1.17448289e-01
   -1.58200268e-01  -3.40939797e-01]
 [  3.89607672e-02   8.39782248e-02  -4.26223644e-02 ...,   5.32916193e-02
    2.89732335e+00  -6.99442448e-02]]
Progress: 78.9% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15924375]
 [-0.94658226]
 [-1.18747986]
 [-0.76758825]
 [-0.0578215 ]
 [ 2.61783632]
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 [-0.83278444]
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 [ 0.14160314]
 [-0.34922448]
 [ 4.47224349]
 [-0.94333413]
 [-1.64540437]
 [ 0.38503063]
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 [-1.90583204]]
[[ -1.85572666e-02  -3.05064884e-01   2.66649885e-01 ...,  -2.32082451e-01
   -3.34028373e-01   2.70645297e-01]
 [  5.84227160e-02   1.45803136e-01   1.14715927e-03 ...,  -2.22177650e-01
    1.59486729e+00   1.13967073e-01]
 [ -6.10931380e-02   2.58945638e-01   4.67624447e-01 ...,   2.34870477e-01
   -3.09176502e-01   9.65814932e-01]
 ..., 
 [ -1.84524921e-01  -2.39777204e-01  -3.82012511e-01 ...,   9.00820793e-02
   -5.93514828e-01  -3.22450757e-01]
 [ -2.75105255e-01  -1.81883676e-01  -1.80344882e-01 ...,  -1.17543252e-01
   -1.58233187e-01  -3.41405036e-01]
 [  3.88768409e-02   8.34424060e-02  -4.34097762e-02 ...,   5.31333048e-02
    2.89777623e+00  -7.11203765e-02]]
Progress: 78.9% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16095364]
 [-0.94862019]
 [-1.18908238]
 [-0.7692157 ]
 [-0.05985545]
 [ 2.61552947]
 [-0.05103249]
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 [ 1.01442644]
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 [-0.10309419]
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 [-0.83452633]
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 [ 0.13988338]
 [-0.35110136]
 [ 4.47199187]
 [-0.94594503]
 [-1.64527495]
 [ 0.38289192]
 [-0.30674703]
 [ 4.29377882]
 [-1.90783568]]
[[ -1.84672612e-02  -3.04589943e-01   2.67229626e-01 ...,  -2.31916492e-01
   -3.36929550e-01   2.71747959e-01]
 [  5.83866939e-02   1.45593740e-01   9.39184097e-04 ...,  -2.22246946e-01
    1.59490161e+00   1.13851704e-01]
 [ -6.08490574e-02   2.60385578e-01   4.69074794e-01 ...,   2.35356955e-01
   -3.12054507e-01   9.68010364e-01]
 ..., 
 [ -1.84568996e-01  -2.40061280e-01  -3.82251421e-01 ...,   8.99997675e-02
   -5.93195316e-01  -3.22950198e-01]
 [ -2.75019867e-01  -1.81404243e-01  -1.79702557e-01 ...,  -1.17386198e-01
   -1.60098897e-01  -3.40616013e-01]
 [  3.89476918e-02   8.38625719e-02  -4.28947199e-02 ...,   5.32626072e-02
    2.89757604e+00  -7.00696899e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16068399]
 [-0.94845587]
 [-1.18933581]
 [-0.76851687]
 [-0.05975738]
 [ 2.61566977]
 [-0.05123578]
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 [ 1.01327549]
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 [ 0.14458361]
 [-0.10375694]
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 [ 0.13940419]
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 [ 4.4715205 ]
 [-0.94589267]
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 [ 0.38255514]
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 [ 4.29444053]
 [-1.90729326]]
[[ -1.84416675e-02  -3.04452215e-01   2.67480301e-01 ...,  -2.31871760e-01
   -3.38409349e-01   2.72218256e-01]
 [  5.83642740e-02   1.45470033e-01   8.97250839e-04 ...,  -2.22288589e-01
    1.59497125e+00   1.13685195e-01]
 [ -6.08737981e-02   2.60231804e-01   4.68734406e-01 ...,   2.35298592e-01
   -3.13038567e-01   9.67219596e-01]
 ..., 
 [ -1.84552742e-01  -2.39965433e-01  -3.82262414e-01 ...,   9.00342824e-02
   -5.93677594e-01  -3.22806444e-01]
 [ -2.75008703e-01  -1.81337104e-01  -1.79696042e-01 ...,  -1.17365661e-01
   -1.60248620e-01  -3.40733936e-01]
 [  3.89241995e-02   8.37170569e-02  -4.32623814e-02 ...,   5.32128932e-02
    2.89777190e+00  -7.04482585e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16027103]
 [-0.94794227]
 [-1.18986645]
 [-0.76787339]
 [-0.05862706]
 [ 2.61710344]
 [-0.04997527]
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 [ 1.01341972]
 [-0.09228637]
 [ 0.144924  ]
 [-0.1017909 ]
 [-0.99507715]
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 [ 0.87164286]
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 [ 4.47237185]
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[[ -1.84669201e-02  -3.04585794e-01   2.67452130e-01 ...,  -2.31915006e-01
   -3.36766260e-01   2.71792423e-01]
 [  5.83197869e-02   1.45204231e-01   5.79637450e-04 ...,  -2.22376116e-01
    1.59594501e+00   1.13106370e-01]
 [ -6.10323621e-02   2.59240143e-01   4.67657826e-01 ...,   2.35011053e-01
   -3.07428360e-01   9.64901104e-01]
 ..., 
 [ -1.84445728e-01  -2.39324180e-01  -3.81589420e-01 ...,   9.02336109e-02
   -5.94743557e-01  -3.22213854e-01]
 [ -2.74950421e-01  -1.81016231e-01  -1.79390499e-01 ...,  -1.17265164e-01
   -1.60807649e-01  -3.40602898e-01]
 [  3.89233339e-02   8.36960528e-02  -4.33884865e-02 ...,   5.32085771e-02
    2.89782954e+00  -7.07038412e-02]]
Progress: 79.0% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.162872  ]
 [-0.94991665]
 [-1.19118145]
 [-0.77009532]
 [-0.06020172]
 [ 2.61628516]
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 [ 1.01276032]
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 [ 0.38216992]
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 [ 4.29041962]
 [-1.90666757]]
[[ -1.83907021e-02  -3.04120686e-01   2.67983680e-01 ...,  -2.31764580e-01
   -3.35812372e-01   2.72699057e-01]
 [  5.83404931e-02   1.45315875e-01   6.30040401e-04 ...,  -2.22340817e-01
    1.59581368e+00   1.13157428e-01]
 [ -6.11161352e-02   2.58721045e-01   4.67465881e-01 ...,   2.34901111e-01
   -3.04832454e-01   9.64980357e-01]
 ..., 
 [ -1.84489521e-01  -2.39583511e-01  -3.81748063e-01 ...,   9.01658253e-02
   -5.93673866e-01  -3.22751646e-01]
 [ -2.74951445e-01  -1.81026760e-01  -1.79442215e-01 ...,  -1.17256538e-01
   -1.60672418e-01  -3.40650841e-01]
 [  3.89842269e-02   8.40448982e-02  -4.28873438e-02 ...,   5.33105332e-02
    2.89781042e+00  -6.97294596e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16150315]
 [-0.94902744]
 [-1.19353897]
 [-0.76706362]
 [-0.05834423]
 [ 2.61605998]
 [-0.05067503]
 [-1.09094017]
 [-0.52852956]
 [ 1.01193266]
 [-0.09379179]
 [ 0.14367353]
 [-0.10244285]
 [-0.99589046]
 [-0.29663468]
 [ 0.86963853]
 [-0.83627178]
 [-0.79721071]
 [-0.61740794]
 [ 0.14025267]
 [-0.35266364]
 [ 4.47081055]
 [-0.94369941]
 [-1.64556972]
 [ 0.38189624]
 [-0.30612061]
 [ 4.29276411]
 [-1.90732331]]
[[ -1.83587863e-02  -3.03919681e-01   2.68122219e-01 ...,  -2.31727911e-01
   -3.36122222e-01   2.73742691e-01]
 [  5.83210891e-02   1.45206879e-01   4.48518580e-04 ...,  -2.22376570e-01
    1.59566864e+00   1.12981837e-01]
 [ -6.08323214e-02   2.60316261e-01   4.68878240e-01 ...,   2.35419105e-01
   -3.07423864e-01   9.66972637e-01]
 ..., 
 [ -1.84433855e-01  -2.39263786e-01  -3.81732079e-01 ...,   9.02761746e-02
   -5.94164602e-01  -3.22156830e-01]
 [ -2.74780325e-01  -1.80057593e-01  -1.78568398e-01 ...,  -1.16959015e-01
   -1.61976566e-01  -3.38614367e-01]
 [  3.89955535e-02   8.41228950e-02  -4.28425940e-02 ...,   5.33292708e-02
    2.89781826e+00  -6.95828509e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16034831]
 [-0.94834722]
 [-1.19222313]
 [-0.76631327]
 [-0.05776686]
 [ 2.61660422]
 [-0.04995748]
 [-1.09116775]
 [-0.52666037]
 [ 1.01276527]
 [-0.09241704]
 [ 0.1445077 ]
 [-0.10219931]
 [-0.99493999]
 [-0.29546729]
 [ 0.86999614]
 [-0.8347689 ]
 [-0.79633984]
 [-0.61640689]
 [ 0.14075065]
 [-0.3521498 ]
 [ 4.47081975]
 [-0.9430629 ]
 [-1.64539647]
 [ 0.38288134]
 [-0.30528968]
 [ 4.29443867]
 [-1.90622496]]
[[ -1.83964188e-02  -3.04136855e-01   2.67580129e-01 ...,  -2.31808993e-01
   -3.36633816e-01   2.73118512e-01]
 [  5.83234152e-02   1.45220516e-01   4.64510570e-04 ...,  -2.22372251e-01
    1.59565209e+00   1.13002908e-01]
 [ -6.10182611e-02   2.59212337e-01   4.67998989e-01 ...,   2.35071296e-01
   -3.05544527e-01   9.65244151e-01]
 ..., 
 [ -1.84492843e-01  -2.39581433e-01  -3.82048289e-01 ...,   9.01699827e-02
   -5.93153662e-01  -3.22485846e-01]
 [ -2.74828822e-01  -1.80337554e-01  -1.79014093e-01 ...,  -1.17046884e-01
   -1.60931933e-01  -3.39297837e-01]
 [  3.89848677e-02   8.40517473e-02  -4.29054972e-02 ...,   5.33000253e-02
    2.89783109e+00  -6.96360348e-02]]
Progress: 79.0% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15805281]
 [-0.94587341]
 [-1.19035889]
 [-0.76404256]
 [-0.05560016]
 [ 2.61957376]
 [-0.04731208]
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 [-0.52415017]
 [ 1.01404849]
 [-0.09032258]
 [ 0.14713437]
 [-0.09934482]
 [-0.99230057]
 [-0.29320512]
 [ 0.87274333]
 [-0.83272125]
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 [-0.61486918]
 [ 0.14301726]
 [-0.35005807]
 [ 4.4714453 ]
 [-0.94131649]
 [-1.64387197]
 [ 0.38509543]
 [-0.3028478 ]
 [ 4.29794165]
 [-1.90460214]]
[[ -1.85307573e-02  -3.04917550e-01   2.67010416e-01 ...,  -2.32062566e-01
   -3.33097543e-01   2.71822963e-01]
 [  5.82549414e-02   1.44811457e-01   1.05242960e-04 ...,  -2.22501248e-01
    1.59651893e+00   1.12339411e-01]
 [ -6.11638428e-02   2.58467119e-01   4.66747981e-01 ...,   2.34814372e-01
   -3.02852790e-01   9.63082118e-01]
 ..., 
 [ -1.84544881e-01  -2.39909536e-01  -3.82336305e-01 ...,   9.00742750e-02
   -5.92063374e-01  -3.23312462e-01]
 [ -2.74848879e-01  -1.80449215e-01  -1.79113202e-01 ...,  -1.17086978e-01
   -1.60921784e-01  -3.39147660e-01]
 [  3.89450519e-02   8.37925375e-02  -4.30208799e-02 ...,   5.32210432e-02
    2.89787920e+00  -7.01208758e-02]]
Progress: 79.0% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16366237]
 [-0.95030572]
 [-1.19348913]
 [-0.76922538]
 [-0.06047121]
 [ 2.61565415]
 [-0.05251707]
 [-1.09291019]
 [-0.52957355]
 [ 1.01099527]
 [-0.09539877]
 [ 0.14224571]
 [-0.10503509]
 [-0.99678278]
 [-0.29825335]
 [ 0.86727924]
 [-0.83800519]
 [-0.79861677]
 [-0.61843065]
 [ 0.1379293 ]
 [-0.35424813]
 [ 4.46981418]
 [-0.94635317]
 [-1.64691822]
 [ 0.38061044]
 [-0.30806182]
 [ 4.29015129]
 [-1.90759621]]
[[ -1.83383096e-02  -3.03810362e-01   2.68210956e-01 ...,  -2.31717961e-01
   -3.35627544e-01   2.73193834e-01]
 [  5.82012986e-02   1.44485778e-01  -2.38506237e-04 ...,  -2.22602315e-01
    1.59731925e+00   1.11837978e-01]
 [ -6.08809693e-02   2.60122670e-01   4.69234940e-01 ...,   2.35322387e-01
   -3.09309432e-01   9.66696066e-01]
 ..., 
 [ -1.84348180e-01  -2.38783840e-01  -3.81148501e-01 ...,   9.04539249e-02
   -5.96642400e-01  -3.21597312e-01]
 [ -2.74712562e-01  -1.79627238e-01  -1.78274339e-01 ...,  -1.16847258e-01
   -1.62305179e-01  -3.37734195e-01]
 [  3.89735983e-02   8.39722654e-02  -4.29396099e-02 ...,   5.32769216e-02
    2.89777212e+00  -6.99428446e-02]]
Progress: 79.0% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.16049689]
 [-0.94800117]
 [-1.19120824]
 [-0.76685972]
 [-0.05782959]
 [ 2.61710942]
 [-0.05027766]
 [-1.09080961]
 [-0.52685898]
 [ 1.01290475]
 [-0.09332553]
 [ 0.14506881]
 [-0.10210644]
 [-0.99471604]
 [-0.29578291]
 [ 0.87083857]
 [-0.83556769]
 [-0.79614306]
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 [ 0.14120926]
 [-0.35119125]
 [ 4.47048277]
 [-0.94467622]
 [-1.64440017]
 [ 0.38323194]
 [-0.30567921]
 [ 4.29452911]
 [-1.90625252]]
[[ -1.85297820e-02  -3.04966994e-01   2.67217076e-01 ...,  -2.32063914e-01
   -3.34739729e-01   2.71028310e-01]
 [  5.81798174e-02   1.44361014e-01  -2.74956293e-04 ...,  -2.22641998e-01
    1.59736744e+00   1.11723959e-01]
 [ -6.08888187e-02   2.60026121e-01   4.69153918e-01 ...,   2.35323701e-01
   -3.08017036e-01   9.66524923e-01]
 ..., 
 [ -1.84351761e-01  -2.38835198e-01  -3.81180426e-01 ...,   9.04551694e-02
   -5.96349610e-01  -3.21741900e-01]
 [ -2.74732162e-01  -1.79755144e-01  -1.78344600e-01 ...,  -1.16884762e-01
   -1.62007879e-01  -3.37903658e-01]
 [  3.90027035e-02   8.40845056e-02  -4.26477419e-02 ...,   5.33265608e-02
    2.89778195e+00  -6.95993983e-02]]
Progress: 79.0% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15773034]
 [-0.94459625]
 [-1.1872087 ]
 [-0.76575459]
 [-0.05681771]
 [ 2.61969621]
 [-0.04718505]
 [-1.09153137]
 [-0.52258706]
 [ 1.0154659 ]
 [-0.09142575]
 [ 0.14740133]
 [-0.09928562]
 [-0.99139161]
 [-0.2927118 ]
 [ 0.8738222 ]
 [-0.83236892]
 [-0.79226839]
 [-0.6124184 ]
 [ 0.14366574]
 [-0.34820242]
 [ 4.47256383]
 [-0.94346466]
 [-1.64427948]
 [ 0.38634841]
 [-0.30270219]
 [ 4.29937409]
 [-1.90318856]]
[[ -1.86714614e-02  -3.05888560e-01   2.65896861e-01 ...,  -2.32345719e-01
   -3.32890712e-01   2.68666478e-01]
 [  5.81583033e-02   1.44207761e-01  -4.51806510e-04 ...,  -2.22686051e-01
    1.59806308e+00   1.11341898e-01]
 [ -6.12866370e-02   2.57734065e-01   4.66581098e-01 ...,   2.34583356e-01
   -3.03839043e-01   9.63146078e-01]
 ..., 
 [ -1.84446152e-01  -2.39398320e-01  -3.81770805e-01 ...,   9.02743806e-02
   -5.94927775e-01  -3.22685989e-01]
 [ -2.74773910e-01  -1.80009662e-01  -1.78773284e-01 ...,  -1.16965025e-01
   -1.61718180e-01  -3.38724831e-01]
 [  3.89494474e-02   8.37208302e-02  -4.30567727e-02 ...,   5.32102494e-02
    2.89776267e+00  -7.01825762e-02]]
Progress: 79.0% ... Training loss: 0.064 ... Validation loss: 0.141[[-0.16205333]
 [-0.94829226]
 [-1.19117934]
 [-0.76968011]
 [-0.06072132]
 [ 2.61848192]
 [-0.0509829 ]
 [-1.09526285]
 [-0.52685846]
 [ 1.01166454]
 [-0.09513911]
 [ 0.14350916]
 [-0.10369186]
 [-0.99432186]
 [-0.29702042]
 [ 0.86816185]
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 [-0.79571154]
 [-0.61628226]
 [ 0.13998391]
 [-0.35258337]
 [ 4.47261567]
 [-0.94616279]
 [-1.64858284]
 [ 0.38351813]
 [-0.30683236]
 [ 4.29320383]
 [-1.90471069]]
[[ -1.85640755e-02  -3.05322096e-01   2.66755014e-01 ...,  -2.32134951e-01
   -3.35708301e-01   2.69373488e-01]
 [  5.81892348e-02   1.44390069e-01  -3.05631784e-04 ...,  -2.22628649e-01
    1.59777858e+00   1.11531443e-01]
 [ -6.12469136e-02   2.57959616e-01   4.66513988e-01 ...,   2.34676468e-01
   -3.07370359e-01   9.63483914e-01]
 ..., 
 [ -1.84428986e-01  -2.39302407e-01  -3.81597591e-01 ...,   9.03074200e-02
   -5.95208010e-01  -3.22507205e-01]
 [ -2.74711790e-01  -1.79645757e-01  -1.78548156e-01 ...,  -1.16830569e-01
   -1.63322280e-01  -3.38537374e-01]
 [  3.89320553e-02   8.36169766e-02  -4.30484077e-02 ...,   5.31704824e-02
    2.89783218e+00  -7.03214028e-02]]
Progress: 79.0% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15731506]
 [-0.94413287]
 [-1.18889036]
 [-0.76457103]
 [-0.05574641]
 [ 2.62123977]
 [-0.04599625]
 [-1.09101362]
 [-0.5230222 ]
 [ 1.01433177]
 [-0.09116501]
 [ 0.1477556 ]
 [-0.09788263]
 [-0.990355  ]
 [-0.29262331]
 [ 0.87274301]
 [-0.83231425]
 [-0.79276021]
 [-0.613691  ]
 [ 0.14474721]
 [-0.34849211]
 [ 4.47425935]
 [-0.94129956]
 [-1.64454575]
 [ 0.38724356]
 [-0.30202606]
 [ 4.30039199]
 [-1.90276339]]
[[ -1.86953268e-02  -3.06058071e-01   2.66008363e-01 ...,  -2.32387314e-01
   -3.32654099e-01   2.68320442e-01]
 [  5.80970308e-02   1.43899139e-01  -7.13947768e-04 ...,  -2.22785297e-01
    1.59852747e+00   1.11009965e-01]
 [ -6.12856223e-02   2.57632544e-01   4.65380247e-01 ...,   2.34584685e-01
   -3.03551663e-01   9.61909472e-01]
 ..., 
 [ -1.84449221e-01  -2.39414089e-01  -3.81592160e-01 ...,   9.02720609e-02
   -5.94629926e-01  -3.22678019e-01]
 [ -2.74824041e-01  -1.80291245e-01  -1.79195102e-01 ...,  -1.17031927e-01
   -1.61666960e-01  -3.39384903e-01]
 [  3.88991684e-02   8.34064410e-02  -4.31544682e-02 ...,   5.30980057e-02
    2.89781955e+00  -7.03526149e-02]]
Progress: 79.0% ... Training loss: 0.065 ... Validation loss: 0.143[[-0.15901892]
 [-0.94632443]
 [-1.18984531]
 [-0.76670941]
 [-0.05751486]
 [ 2.61945516]
 [-0.04783903]
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 [-0.52545769]
 [ 1.01264316]
 [-0.0921249 ]
 [ 0.14651367]
 [-0.09944266]
 [-0.99324147]
 [-0.2940086 ]
 [ 0.87198044]
 [-0.83412357]
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 [ 0.14306791]
 [-0.34985755]
 [ 4.47425852]
 [-0.94404552]
 [-1.6446624 ]
 [ 0.38600855]
 [-0.30414468]
 [ 4.29816894]
 [-1.90439807]]
[[ -1.87897767e-02  -3.06582640e-01   2.65710475e-01 ...,  -2.32558074e-01
   -3.31655598e-01   2.67910847e-01]
 [  5.80381490e-02   1.43556831e-01  -9.07377594e-04 ...,  -2.22891982e-01
    1.59880051e+00   1.10722735e-01]
 [ -6.10490990e-02   2.58996002e-01   4.66748631e-01 ...,   2.35038012e-01
   -3.09398669e-01   9.65012602e-01]
 ..., 
 [ -1.84450811e-01  -2.39420113e-01  -3.81660005e-01 ...,   9.02751457e-02
   -5.95243587e-01  -3.22491949e-01]
 [ -2.74931873e-01  -1.80889332e-01  -1.79474376e-01 ...,  -1.17234864e-01
   -1.60209057e-01  -3.39868293e-01]
 [  3.87701429e-02   8.26311061e-02  -4.38233122e-02 ...,   5.28516240e-02
    2.89801545e+00  -7.19196633e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16400483]
 [-0.94985829]
 [-1.19349366]
 [-0.77083643]
 [-0.06054124]
 [ 2.61572052]
 [-0.05235711]
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 [-0.52969403]
 [ 1.01079776]
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 [ 0.14277514]
 [-0.10347611]
 [-0.99743902]
 [-0.29829335]
 [ 0.86771263]
 [-0.83881734]
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 [ 0.13989802]
 [-0.353519  ]
 [ 4.4739315 ]
 [-0.94822367]
 [-1.64738861]
 [ 0.3821617 ]
 [-0.30766281]
 [ 4.29086777]
 [-1.90766899]]
[[ -1.85973580e-02  -3.05466147e-01   2.66949283e-01 ...,  -2.32196102e-01
   -3.32808351e-01   2.69635820e-01]
 [  5.80949310e-02   1.43906026e-01  -5.03319199e-04 ...,  -2.22803689e-01
    1.59876315e+00   1.11414359e-01]
 [ -6.08172513e-02   2.60480966e-01   4.68333661e-01 ...,   2.35485698e-01
   -3.11698906e-01   9.67952371e-01]
 ..., 
 [ -1.84380106e-01  -2.39041766e-01  -3.81269490e-01 ...,   9.04006060e-02
   -5.96847565e-01  -3.21933996e-01]
 [ -2.74828120e-01  -1.80272235e-01  -1.79275575e-01 ...,  -1.17039463e-01
   -1.61793636e-01  -3.39115596e-01]
 [  3.87926623e-02   8.27478631e-02  -4.36859189e-02 ...,   5.28870719e-02
    2.89804796e+00  -7.17134702e-02]]
Progress: 79.0% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.15990816]
 [-0.94672597]
 [-1.18967054]
 [-0.76743051]
 [-0.05756882]
 [ 2.61605409]
 [-0.04896183]
 [-1.09145351]
 [-0.525908  ]
 [ 1.0141222 ]
 [-0.09276957]
 [ 0.14563075]
 [-0.10023475]
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 [ 0.87155462]
 [-0.83452505]
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 [ 0.14283397]
 [-0.34974029]
 [ 4.4763077 ]
 [-0.94557977]
 [-1.64388715]
 [ 0.38491111]
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 [ 4.29736084]
 [-1.90560636]]
[[ -1.87076836e-02  -3.06091503e-01   2.65888495e-01 ...,  -2.32381898e-01
   -3.32990579e-01   2.68060647e-01]
 [  5.80762587e-02   1.43790331e-01  -6.40463005e-04 ...,  -2.22839537e-01
    1.59886457e+00   1.11238858e-01]
 [ -6.08590623e-02   2.60195628e-01   4.68132314e-01 ...,   2.35424045e-01
   -3.11032992e-01   9.66754914e-01]
 ..., 
 [ -1.84440105e-01  -2.39368256e-01  -3.81499441e-01 ...,   9.02988935e-02
   -5.95958325e-01  -3.22370328e-01]
 [ -2.74871978e-01  -1.80518727e-01  -1.79624285e-01 ...,  -1.17118024e-01
   -1.61303402e-01  -3.39553143e-01]
 [  3.87937843e-02   8.27395093e-02  -4.38408650e-02 ...,   5.28808945e-02
    2.89802590e+00  -7.18981818e-02]]
Progress: 79.0% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16672022]
 [-0.95235478]
 [-1.19608097]
 [-0.77248541]
 [-0.06337335]
 [ 2.61417743]
 [-0.05355467]
 [-1.09677194]
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 [ 1.00932776]
 [-0.09895804]
 [ 0.13941103]
 [-0.10550769]
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 [-0.301702  ]
 [ 0.86344496]
 [-0.84149909]
 [-0.79974686]
 [-0.62176794]
 [ 0.1373758 ]
 [-0.35568184]
 [ 4.47570874]
 [-0.94860626]
 [-1.65089664]
 [ 0.38042382]
 [-0.30999981]
 [ 4.28720463]
 [-1.90747771]]
[[ -1.85599300e-02  -3.05238419e-01   2.66980153e-01 ...,  -2.32123730e-01
   -3.35324346e-01   2.69063712e-01]
 [  5.80719954e-02   1.43745779e-01  -6.00133945e-04 ...,  -2.22850463e-01
    1.59880372e+00   1.11148556e-01]
 [ -6.08747312e-02   2.60108669e-01   4.68354588e-01 ...,   2.35397978e-01
   -3.12850670e-01   9.68029867e-01]
 ..., 
 [ -1.84379757e-01  -2.39028674e-01  -3.81028594e-01 ...,   9.04076461e-02
   -5.97839286e-01  -3.21691415e-01]
 [ -2.74848596e-01  -1.80391466e-01  -1.79358706e-01 ...,  -1.17086015e-01
   -1.61707782e-01  -3.39658491e-01]
 [  3.89338924e-02   8.35475503e-02  -4.31012705e-02 ...,   5.31454729e-02
    2.89782445e+00  -7.16692829e-02]]
Progress: 79.1% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.1608915 ]
 [-0.94826481]
 [-1.19115473]
 [-0.7683703 ]
 [-0.05948499]
 [ 2.61852098]
 [-0.04848313]
 [-1.09350814]
 [-0.52725581]
 [ 1.01252608]
 [-0.09370252]
 [ 0.144361  ]
 [-0.10016687]
 [-0.99306742]
 [-0.29662873]
 [ 0.8689609 ]
 [-0.83555271]
 [-0.79450103]
 [-0.61753198]
 [ 0.14166702]
 [-0.35155273]
 [ 4.478139  ]
 [-0.94351824]
 [-1.64658846]
 [ 0.38491648]
 [-0.30554961]
 [ 4.29601386]
 [-1.90430326]]
[[ -1.89479153e-02  -3.07348179e-01   2.64849997e-01 ...,  -2.32820713e-01
   -3.30643498e-01   2.65909994e-01]
 [  5.81200983e-02   1.44012407e-01  -3.20275757e-04 ...,  -2.22766171e-01
    1.59848276e+00   1.11483331e-01]
 [ -6.10886710e-02   2.58836750e-01   4.66518807e-01 ...,   2.35008463e-01
   -3.09158016e-01   9.64888686e-01]
 ..., 
 [ -1.84461130e-01  -2.39482755e-01  -3.81552823e-01 ...,   9.02613840e-02
   -5.96356984e-01  -3.22519517e-01]
 [ -2.74873695e-01  -1.80525321e-01  -1.79584486e-01 ...,  -1.17120775e-01
   -1.61042534e-01  -3.39862780e-01]
 [  3.87813968e-02   8.27032623e-02  -4.37336249e-02 ...,   5.28688846e-02
    2.89813093e+00  -7.28005043e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16296914]
 [-0.94947855]
 [-1.19144424]
 [-0.769842  ]
 [-0.06045459]
 [ 2.61508154]
 [-0.0509765 ]
 [-1.09353213]
 [-0.52878034]
 [ 1.01273479]
 [-0.09496742]
 [ 0.14298895]
 [-0.10257631]
 [-0.99658169]
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 [ 0.86753149]
 [-0.83676555]
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 [ 0.13973978]
 [-0.35283882]
 [ 4.47754403]
 [-0.94659385]
 [-1.64619604]
 [ 0.38244741]
 [-0.30713265]
 [ 4.29412835]
 [-1.9064731 ]]
[[ -1.87626208e-02  -3.06285076e-01   2.66077077e-01 ...,  -2.32480986e-01
   -3.33729974e-01   2.67903589e-01]
 [  5.81227512e-02   1.44024724e-01  -3.16077957e-04 ...,  -2.22761040e-01
    1.59840937e+00   1.11498405e-01]
 [ -6.08341990e-02   2.60261166e-01   4.68362426e-01 ...,   2.35487847e-01
   -3.13884801e-01   9.67562844e-01]
 ..., 
 [ -1.84458073e-01  -2.39459555e-01  -3.81560686e-01 ...,   9.02666359e-02
   -5.96804509e-01  -3.22590046e-01]
 [ -2.74860074e-01  -1.80441987e-01  -1.79355108e-01 ...,  -1.17091684e-01
   -1.61988400e-01  -3.39534218e-01]
 [  3.87901937e-02   8.27668082e-02  -4.36851836e-02 ...,   5.28849251e-02
    2.89805694e+00  -7.24892046e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16407353]
 [-0.95016238]
 [-1.19259302]
 [-0.77023463]
 [-0.06085242]
 [ 2.61604067]
 [-0.05134725]
 [-1.09519466]
 [-0.52925968]
 [ 1.0112727 ]
 [-0.09628581]
 [ 0.14186216]
 [-0.10288346]
 [-0.99598955]
 [-0.29906813]
 [ 0.86581153]
 [-0.8378405 ]
 [-0.79697087]
 [-0.61946894]
 [ 0.13914542]
 [-0.354049  ]
 [ 4.47706037]
 [-0.94626656]
 [-1.64802345]
 [ 0.38201629]
 [-0.307575  ]
 [ 4.29225354]
 [-1.90614922]]
[[ -1.87922357e-02  -3.06428572e-01   2.65891810e-01 ...,  -2.32553886e-01
   -3.32045150e-01   2.68267610e-01]
 [  5.81354049e-02   1.44096002e-01  -2.96926811e-04 ...,  -2.22739701e-01
    1.59837825e+00   1.11536495e-01]
 [ -6.09895046e-02   2.59378862e-01   4.67394110e-01 ...,   2.35181933e-01
   -3.10714935e-01   9.66647911e-01]
 ..., 
 [ -1.84371357e-01  -2.38975879e-01  -3.81060295e-01 ...,   9.04303861e-02
   -5.97397723e-01  -3.22253262e-01]
 [ -2.74917291e-01  -1.80778211e-01  -1.79739318e-01 ...,  -1.17201667e-01
   -1.60778134e-01  -3.40186780e-01]
 [  3.87969964e-02   8.28141436e-02  -4.35203042e-02 ...,   5.28945998e-02
    2.89794808e+00  -7.22933458e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.1628498 ]
 [-0.94862382]
 [-1.19132903]
 [-0.77002085]
 [-0.0601052 ]
 [ 2.61831105]
 [-0.04990321]
 [-1.09570143]
 [-0.52741022]
 [ 1.01262096]
 [-0.09511434]
 [ 0.14319633]
 [-0.10182639]
 [-0.99410913]
 [-0.29785864]
 [ 0.8674498 ]
 [-0.83665838]
 [-0.79472403]
 [-0.61823052]
 [ 0.14006343]
 [-0.35313164]
 [ 4.47760687]
 [-0.94536512]
 [-1.64820355]
 [ 0.38400735]
 [-0.30677874]
 [ 4.29393441]
 [-1.90496967]]
[[ -1.88622793e-02  -3.06879918e-01   2.65589128e-01 ...,  -2.32661443e-01
   -3.29804470e-01   2.67983317e-01]
 [  5.81402687e-02   1.44123884e-01  -2.52540404e-04 ...,  -2.22732740e-01
    1.59833742e+00   1.11603150e-01]
 [ -6.12403085e-02   2.57929771e-01   4.66199104e-01 ...,   2.34715464e-01
   -3.06240897e-01   9.65016256e-01]
 ..., 
 [ -1.84364046e-01  -2.38934611e-01  -3.81061010e-01 ...,   9.04468823e-02
   -5.97648082e-01  -3.22317939e-01]
 [ -2.75003262e-01  -1.81282839e-01  -1.80340646e-01 ...,  -1.17346696e-01
   -1.58635900e-01  -3.40984267e-01]
 [  3.87815103e-02   8.27221291e-02  -4.36263477e-02 ...,   5.28685065e-02
    2.89802643e+00  -7.20782232e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16205638]
 [-0.9490099 ]
 [-1.19226494]
 [-0.76885083]
 [-0.05907348]
 [ 2.61720887]
 [-0.05016683]
 [-1.09356484]
 [-0.52776988]
 [ 1.01212608]
 [-0.09447953]
 [ 0.1435753 ]
 [-0.10188192]
 [-0.99609044]
 [-0.29783008]
 [ 0.86831628]
 [-0.83630967]
 [-0.79472076]
 [-0.618465  ]
 [ 0.14053668]
 [-0.35290814]
 [ 4.47786731]
 [-0.94459116]
 [-1.64556415]
 [ 0.38344448]
 [-0.30679703]
 [ 4.29422262]
 [-1.90619497]]
[[ -1.88475877e-02  -3.06704639e-01   2.65336224e-01 ...,  -2.32606701e-01
   -3.30523873e-01   2.68445867e-01]
 [  5.82830019e-02   1.44883491e-01   2.40377968e-04 ...,  -2.22475909e-01
    1.59802212e+00   1.13025996e-01]
 [ -6.09239900e-02   2.59706528e-01   4.67368534e-01 ...,   2.35319007e-01
   -3.07645835e-01   9.66866494e-01]
 ..., 
 [ -1.84368685e-01  -2.38931718e-01  -3.81246730e-01 ...,   9.04361567e-02
   -5.96089430e-01  -3.22163585e-01]
 [ -2.75038997e-01  -1.81452429e-01  -1.80521310e-01 ...,  -1.17404948e-01
   -1.57527663e-01  -3.41390328e-01]
 [  3.86512505e-02   8.19831390e-02  -4.45147404e-02 ...,   5.26304947e-02
    2.89814752e+00  -7.28075797e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16034433]
 [-0.94677869]
 [-1.19093458]
 [-0.76725074]
 [-0.05721631]
 [ 2.61907578]
 [-0.04818562]
 [-1.09221519]
 [-0.52520525]
 [ 1.01367252]
 [-0.09348454]
 [ 0.14546194]
 [-0.09932871]
 [-0.99457412]
 [-0.29572144]
 [ 0.87088577]
 [-0.8348361 ]
 [-0.79328357]
 [-0.61651625]
 [ 0.14261483]
 [-0.3511321 ]
 [ 4.47767306]
 [-0.94371723]
 [-1.64458285]
 [ 0.38545626]
 [-0.30448177]
 [ 4.29692123]
 [-1.90508573]]
[[ -1.88012763e-02  -3.06401844e-01   2.65725297e-01 ...,  -2.32513905e-01
   -3.29629397e-01   2.69090160e-01]
 [  5.83313088e-02   1.45179245e-01   5.79828035e-04 ...,  -2.22402078e-01
    1.59805498e+00   1.13645345e-01]
 [ -6.10698013e-02   2.58938902e-01   4.66535889e-01 ...,   2.35059380e-01
   -3.03519256e-01   9.65419684e-01]
 ..., 
 [ -1.84385476e-01  -2.39038672e-01  -3.81317233e-01 ...,   9.04078462e-02
   -5.95587656e-01  -3.22288104e-01]
 [ -2.75107264e-01  -1.81871847e-01  -1.80936787e-01 ...,  -1.17542183e-01
   -1.57010111e-01  -3.42063128e-01]
 [  3.85503309e-02   8.13970912e-02  -4.50263189e-02 ...,   5.24535306e-02
    2.89844257e+00  -7.36346793e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16423038]
 [-0.95001956]
 [-1.19380369]
 [-0.77043024]
 [-0.05972932]
 [ 2.61668494]
 [-0.05156967]
 [-1.0942345 ]
 [-0.52881505]
 [ 1.01252601]
 [-0.09608458]
 [ 0.14238622]
 [-0.10368453]
 [-0.99841687]
 [-0.29909537]
 [ 0.86734875]
 [-0.8385972 ]
 [-0.79653364]
 [-0.61914713]
 [ 0.13923102]
 [-0.35444959]
 [ 4.47711713]
 [-0.94722461]
 [-1.64703292]
 [ 0.38252338]
 [-0.30796932]
 [ 4.2909703 ]
 [-1.90793474]]
[[ -1.86159598e-02  -3.05386996e-01   2.66842096e-01 ...,  -2.32186889e-01
   -3.33358147e-01   2.71582292e-01]
 [  5.83450536e-02   1.45258282e-01   6.33157121e-04 ...,  -2.22379535e-01
    1.59792383e+00   1.13749503e-01]
 [ -6.09500965e-02   2.59619483e-01   4.67601549e-01 ...,   2.35280403e-01
   -3.06824882e-01   9.67387504e-01]
 ..., 
 [ -1.84330709e-01  -2.38727975e-01  -3.80974604e-01 ...,   9.05082831e-02
   -5.96595438e-01  -3.21699735e-01]
 [ -2.75082176e-01  -1.81726156e-01  -1.80741967e-01 ...,  -1.17497498e-01
   -1.57400178e-01  -3.41760411e-01]
 [  3.86709558e-02   8.21004678e-02  -4.42646529e-02 ...,   5.26736686e-02
    2.89833546e+00  -7.26167458e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16134066]
 [-0.9486189 ]
 [-1.19268312]
 [-0.76678837]
 [-0.05683946]
 [ 2.61731226]
 [-0.04921611]
 [-1.0913453 ]
 [-0.52691402]
 [ 1.01339586]
 [-0.09471587]
 [ 0.14450354]
 [-0.10066434]
 [-0.99714491]
 [-0.29724156]
 [ 0.87018649]
 [-0.83657764]
 [-0.79533412]
 [-0.61852507]
 [ 0.14185554]
 [-0.35216456]
 [ 4.47700287]
 [-0.94403698]
 [-1.64364571]
 [ 0.38377416]
 [-0.30580575]
 [ 4.29500147]
 [-1.90733232]]
[[ -1.87150091e-02  -3.05892933e-01   2.66437896e-01 ...,  -2.32355480e-01
   -3.32062678e-01   2.71579369e-01]
 [  5.84005604e-02   1.45601636e-01   1.00773783e-03 ...,  -2.22282238e-01
    1.59801770e+00   1.14637132e-01]
 [ -6.08054557e-02   2.60421961e-01   4.67848978e-01 ...,   2.35534024e-01
   -3.06874159e-01   9.68356583e-01]
 ..., 
 [ -1.84279151e-01  -2.38427183e-01  -3.80474064e-01 ...,   9.06010017e-02
   -5.96897020e-01  -3.21637523e-01]
 [ -2.75219246e-01  -1.82498057e-01  -1.81818175e-01 ...,  -1.17729230e-01
   -1.55791271e-01  -3.43024360e-01]
 [  3.86585066e-02   8.20516260e-02  -4.42785539e-02 ...,   5.26517030e-02
    2.89851134e+00  -7.27088334e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15987283]
 [-0.94749034]
 [-1.18928941]
 [-0.76702071]
 [-0.05719142]
 [ 2.61970516]
 [-0.04794229]
 [-1.09183863]
 [-0.52531652]
 [ 1.01364058]
 [-0.09326168]
 [ 0.14588916]
 [-0.09932141]
 [-0.99492214]
 [-0.29557114]
 [ 0.87162559]
 [-0.83440568]
 [-0.79243913]
 [-0.61690304]
 [ 0.14209789]
 [-0.35105528]
 [ 4.47748777]
 [-0.9438173 ]
 [-1.64347268]
 [ 0.38589894]
 [-0.30515552]
 [ 4.2988368 ]
 [-1.90562947]]
[[ -1.89222969e-02  -3.07084384e-01   2.65067948e-01 ...,  -2.32720487e-01
   -3.32294507e-01   2.69849488e-01]
 [  5.83700020e-02   1.45440352e-01   7.79817712e-04 ...,  -2.22336394e-01
    1.59840319e+00   1.14522770e-01]
 [ -6.10836732e-02   2.58817274e-01   4.66660214e-01 ...,   2.35021916e-01
   -3.06768893e-01   9.66850603e-01]
 ..., 
 [ -1.84161732e-01  -2.37742345e-01  -3.79870096e-01 ...,   9.08042686e-02
   -5.98521939e-01  -3.20795934e-01]
 [ -2.75289498e-01  -1.82920950e-01  -1.82358180e-01 ...,  -1.17842250e-01
   -1.55827300e-01  -3.43886749e-01]
 [  3.84989797e-02   8.11309589e-02  -4.52389394e-02 ...,   5.23611883e-02
    2.89894216e+00  -7.45123903e-02]]
Progress: 79.1% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16077887]
 [-0.94889509]
 [-1.18959082]
 [-0.76837024]
 [-0.05803116]
 [ 2.62024706]
 [-0.0489856 ]
 [-1.0936979 ]
 [-0.52635007]
 [ 1.01246366]
 [-0.09464772]
 [ 0.14475151]
 [-0.10026289]
 [-0.99526052]
 [-0.29647264]
 [ 0.870552  ]
 [-0.83549585]
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 [-0.61789029]
 [ 0.14094232]
 [-0.35244035]
 [ 4.47763033]
 [-0.94515417]
 [-1.64554656]
 [ 0.38527298]
 [-0.30635929]
 [ 4.29618281]
 [-1.90577337]]
[[ -1.89507372e-02  -3.07204593e-01   2.64824837e-01 ...,  -2.32765858e-01
   -3.31152094e-01   2.69922566e-01]
 [  5.83945153e-02   1.45577546e-01   9.19466445e-04 ...,  -2.22291660e-01
    1.59825618e+00   1.14641267e-01]
 [ -6.11691200e-02   2.58337948e-01   4.66227304e-01 ...,   2.34865829e-01
   -3.07424820e-01   9.65860509e-01]
 ..., 
 [ -1.84096032e-01  -2.37366788e-01  -3.79485185e-01 ...,   9.09254714e-02
   -5.99640659e-01  -3.20386184e-01]
 [ -2.75231744e-01  -1.82590659e-01  -1.82105515e-01 ...,  -1.17736524e-01
   -1.56498855e-01  -3.43645421e-01]
 [  3.84432144e-02   8.08127128e-02  -4.57040515e-02 ...,   5.22587848e-02
    2.89905154e+00  -7.51503243e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16159917]
 [-0.950643  ]
 [-1.19097964]
 [-0.76806017]
 [-0.05833924]
 [ 2.61884493]
 [-0.04960834]
 [-1.0921268 ]
 [-0.52869166]
 [ 1.0115245 ]
 [-0.09456781]
 [ 0.14422738]
 [-0.1008203 ]
 [-0.99694936]
 [-0.29764001]
 [ 0.87014446]
 [-0.8364914 ]
 [-0.79462116]
 [-0.61933006]
 [ 0.13974   ]
 [-0.35313028]
 [ 4.47756991]
 [-0.94502564]
 [-1.64416533]
 [ 0.38409996]
 [-0.30775279]
 [ 4.29556278]
 [-1.9076562 ]]
[[ -1.90004380e-02  -3.07409444e-01   2.64811748e-01 ...,  -2.32838420e-01
   -3.32053505e-01   2.70158749e-01]
 [  5.83464542e-02   1.45314910e-01   7.82769706e-04 ...,  -2.22376692e-01
    1.59867678e+00   1.14329889e-01]
 [ -6.08188202e-02   2.60337704e-01   4.68393634e-01 ...,   2.35533840e-01
   -3.09657114e-01   9.69111708e-01]
 ..., 
 [ -1.84093612e-01  -2.37346984e-01  -3.79515471e-01 ...,   9.09301085e-02
   -5.99619777e-01  -3.20458283e-01]
 [ -2.75258964e-01  -1.82722630e-01  -1.82218423e-01 ...,  -1.17785505e-01
   -1.56501189e-01  -3.43921690e-01]
 [  3.84283888e-02   8.07559278e-02  -4.58221108e-02 ...,   5.22306662e-02
    2.89916294e+00  -7.51175298e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.1553327 ]
 [-0.94526735]
 [-1.18449957]
 [-0.7639158 ]
 [-0.05457542]
 [ 2.62361818]
 [-0.04471498]
 [-1.0903618 ]
 [-0.5219407 ]
 [ 1.01537134]
 [-0.08911494]
 [ 0.14912985]
 [-0.09593897]
 [-0.99170011]
 [-0.29208176]
 [ 0.87617082]
 [-0.83003619]
 [-0.78787507]
 [-0.61374676]
 [ 0.14403745]
 [-0.34813069]
 [ 4.47855937]
 [-0.94069087]
 [-1.64063396]
 [ 0.38941832]
 [-0.30359777]
 [ 4.30561677]
 [-1.90342116]]
[[ -1.92617583e-02  -3.08902382e-01   2.63071163e-01 ...,  -2.33297069e-01
   -3.29929912e-01   2.67313136e-01]
 [  5.82509069e-02   1.44748113e-01   1.68598077e-04 ...,  -2.22555920e-01
    1.59922827e+00   1.13331176e-01]
 [ -6.12869822e-02   2.57570592e-01   4.65475906e-01 ...,   2.34677479e-01
   -3.05358952e-01   9.63684052e-01]
 ..., 
 [ -1.84083879e-01  -2.37292582e-01  -3.79576194e-01 ...,   9.09432860e-02
   -5.99447062e-01  -3.20523739e-01]
 [ -2.75348059e-01  -1.83233835e-01  -1.82850306e-01 ...,  -1.17938610e-01
   -1.54192066e-01  -3.44836364e-01]
 [  3.83558772e-02   8.03492482e-02  -4.63305736e-02 ...,   5.21009118e-02
    2.89921654e+00  -7.60135187e-02]]
Progress: 79.1% ... Training loss: 0.067 ... Validation loss: 0.152[[-0.16173908]
 [-0.95046025]
 [-1.18912636]
 [-0.76911285]
 [-0.0598598 ]
 [ 2.61980629]
 [-0.05019685]
 [-1.09514392]
 [-0.5273784 ]
 [ 1.01139745]
 [-0.09446994]
 [ 0.1435074 ]
 [-0.10217237]
 [-0.99626292]
 [-0.29780888]
 [ 0.86950845]
 [-0.83595096]
 [-0.79350619]
 [-0.61856572]
 [ 0.13861792]
 [-0.35341742]
 [ 4.47696689]
 [-0.94606426]
 [-1.64621091]
 [ 0.38474012]
 [-0.30865694]
 [ 4.29667556]
 [-1.90629311]]
[[ -1.90126769e-02  -3.07445362e-01   2.64584970e-01 ...,  -2.32847348e-01
   -3.35770593e-01   2.69586089e-01]
 [  5.82556459e-02   1.44765336e-01   1.34007388e-04 ...,  -2.22543623e-01
    1.59900602e+00   1.13446651e-01]
 [ -6.12028071e-02   2.58154012e-01   4.66095328e-01 ...,   2.34839161e-01
   -3.09193382e-01   9.66307540e-01]
 ..., 
 [ -1.84005608e-01  -2.36823487e-01  -3.79287521e-01 ...,   9.10951615e-02
   -6.01063190e-01  -3.20195250e-01]
 [ -2.75284092e-01  -1.82882547e-01  -1.82486800e-01 ...,  -1.17834603e-01
   -1.54930208e-01  -3.44479486e-01]
 [  3.84178973e-02   8.07357371e-02  -4.61143813e-02 ...,   5.22265349e-02
    2.89922334e+00  -7.57206039e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15931228]
 [-0.94780664]
 [-1.18796839]
 [-0.76623551]
 [-0.05749459]
 [ 2.62071262]
 [-0.04828992]
 [-1.09304123]
 [-0.5254405 ]
 [ 1.01300649]
 [-0.09263592]
 [ 0.14510057]
 [-0.10001275]
 [-0.9949756 ]
 [-0.29598008]
 [ 0.87093101]
 [-0.83369931]
 [-0.79200862]
 [-0.61717383]
 [ 0.14064334]
 [-0.35130373]
 [ 4.47750615]
 [-0.94339403]
 [-1.64391666]
 [ 0.38601554]
 [-0.306358  ]
 [ 4.30098048]
 [-1.90546262]]
[[ -1.89109821e-02  -3.06942425e-01   2.65210473e-01 ...,  -2.32659991e-01
   -3.37210331e-01   2.70424542e-01]
 [  5.82376014e-02   1.44650779e-01   1.92188330e-04 ...,  -2.22578238e-01
    1.59902140e+00   1.13415773e-01]
 [ -6.12446520e-02   2.57973733e-01   4.65429899e-01 ...,   2.34788925e-01
   -3.08545712e-01   9.65417335e-01]
 ..., 
 [ -1.83998483e-01  -2.36805104e-01  -3.79443449e-01 ...,   9.11208659e-02
   -6.01207995e-01  -3.20438562e-01]
 [ -2.75300171e-01  -1.82990136e-01  -1.82409360e-01 ...,  -1.17880309e-01
   -1.55124171e-01  -3.44471956e-01]
 [  3.84098699e-02   8.06838556e-02  -4.61481136e-02 ...,   5.22032036e-02
    2.89920147e+00  -7.58171991e-02]]
Progress: 79.1% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16122264]
 [-0.94910549]
 [-1.18981388]
 [-0.76713467]
 [-0.05904264]
 [ 2.6195821 ]
 [-0.05003456]
 [-1.09375264]
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 [ 1.01258576]
 [-0.09408509]
 [ 0.1430007 ]
 [-0.10208697]
 [-0.99688596]
 [-0.29784171]
 [ 0.86846838]
 [-0.83518299]
 [-0.79360714]
 [-0.61886631]
 [ 0.13863446]
 [-0.35307572]
 [ 4.47670626]
 [-0.9443706 ]
 [-1.64441474]
 [ 0.38429499]
 [-0.30793051]
 [ 4.29880031]
 [-1.90673038]]
[[ -1.86615996e-02  -3.05513121e-01   2.66777108e-01 ...,  -2.32207883e-01
   -3.41941901e-01   2.72599431e-01]
 [  5.82159582e-02   1.44507899e-01  -8.77382019e-06 ...,  -2.22624495e-01
    1.59899630e+00   1.13300764e-01]
 [ -6.11488586e-02   2.58585997e-01   4.66243548e-01 ...,   2.34988198e-01
   -3.09800274e-01   9.66298318e-01]
 ..., 
 [ -1.83969791e-01  -2.36674886e-01  -3.79298132e-01 ...,   9.11796435e-02
   -6.01548026e-01  -3.20238611e-01]
 [ -2.75351998e-01  -1.83303976e-01  -1.82606311e-01 ...,  -1.17971146e-01
   -1.55469603e-01  -3.44448524e-01]
 [  3.84514737e-02   8.09245065e-02  -4.60799085e-02 ...,   5.22730280e-02
    2.89909791e+00  -7.56647175e-02]]
Progress: 79.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16019881]
 [-0.94732515]
 [-1.18711549]
 [-0.76660223]
 [-0.05792558]
 [ 2.62158311]
 [-0.04895445]
 [-1.0938835 ]
 [-0.5250721 ]
 [ 1.0134499 ]
 [-0.09305133]
 [ 0.14427903]
 [-0.10038681]
 [-0.9959152 ]
 [-0.2958687 ]
 [ 0.87009303]
 [-0.83318297]
 [-0.79248562]
 [-0.61633622]
 [ 0.139226  ]
 [-0.3520165 ]
 [ 4.47710799]
 [-0.94473688]
 [-1.64417999]
 [ 0.385405  ]
 [-0.30591705]
 [ 4.30142578]
 [-1.90558838]]
[[ -1.86857414e-02  -3.05668293e-01   2.66273044e-01 ...,  -2.32245379e-01
   -3.42868555e-01   2.71959026e-01]
 [  5.82226621e-02   1.44536757e-01   2.48157713e-05 ...,  -2.22610298e-01
    1.59898112e+00   1.13559140e-01]
 [ -6.13939595e-02   2.57243094e-01   4.65110779e-01 ...,   2.34524924e-01
   -3.07958401e-01   9.64080843e-01]
 ..., 
 [ -1.83997739e-01  -2.36854277e-01  -3.79526938e-01 ...,   9.11236345e-02
   -6.00970805e-01  -3.20483304e-01]
 [ -2.75357697e-01  -1.83349054e-01  -1.82724425e-01 ...,  -1.17981389e-01
   -1.55654742e-01  -3.44607276e-01]
 [  3.83768852e-02   8.04604209e-02  -4.65938888e-02 ...,   5.21252299e-02
    2.89929009e+00  -7.66927288e-02]]
Progress: 79.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16031036]
 [-0.94691641]
 [-1.18820288]
 [-0.76524291]
 [-0.05696103]
 [ 2.62321738]
 [-0.04820273]
 [-1.0922324 ]
 [-0.52579737]
 [ 1.01140474]
 [-0.09387124]
 [ 0.14523501]
 [-0.09859814]
 [-0.9953184 ]
 [-0.29554219]
 [ 0.87095725]
 [-0.83356195]
 [-0.79447601]
 [-0.61783898]
 [ 0.14032338]
 [-0.35134019]
 [ 4.47623283]
 [-0.94440216]
 [-1.64371123]
 [ 0.3859181 ]
 [-0.3052326 ]
 [ 4.3026725 ]
 [-1.90594894]]
[[ -1.88867817e-02  -3.06863363e-01   2.65518920e-01 ...,  -2.32612300e-01
   -3.42061541e-01   2.70139468e-01]
 [  5.82087994e-02   1.44471835e-01   4.50362534e-05 ...,  -2.22640853e-01
    1.59918988e+00   1.13689775e-01]
 [ -6.12860918e-02   2.57813738e-01   4.66150955e-01 ...,   2.34740633e-01
   -3.09873073e-01   9.65181832e-01]
 ..., 
 [ -1.83922141e-01  -2.36391972e-01  -3.78935240e-01 ...,   9.12533953e-02
   -6.01082074e-01  -3.19723073e-01]
 [ -2.75395205e-01  -1.83554749e-01  -1.82690869e-01 ...,  -1.18058030e-01
   -1.56154527e-01  -3.44708258e-01]
 [  3.82547679e-02   7.97411112e-02  -4.69882793e-02 ...,   5.18995881e-02
    2.89953591e+00  -7.78792106e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15673974]
 [-0.94456542]
 [-1.18494114]
 [-0.76261469]
 [-0.05447247]
 [ 2.62489188]
 [-0.04592824]
 [-1.08988309]
 [-0.52255189]
 [ 1.0138627 ]
 [-0.09063636]
 [ 0.14850321]
 [-0.09571413]
 [-0.99366688]
 [-0.29210124]
 [ 0.87527044]
 [-0.82937855]
 [-0.79066969]
 [-0.61423584]
 [ 0.14350278]
 [-0.34715673]
 [ 4.47661464]
 [-0.94252638]
 [-1.64032503]
 [ 0.38882329]
 [-0.30291482]
 [ 4.30862553]
 [-1.90485455]]
[[ -1.90219938e-02  -3.07616445e-01   2.64631526e-01 ...,  -2.32832534e-01
   -3.40965968e-01   2.69176804e-01]
 [  5.82278968e-02   1.44582412e-01   4.53526845e-05 ...,  -2.22608858e-01
    1.59926080e+00   1.13771813e-01]
 [ -6.13120819e-02   2.57602724e-01   4.66506653e-01 ...,   2.34695427e-01
   -3.09254284e-01   9.64633938e-01]
 ..., 
 [ -1.83923804e-01  -2.36391882e-01  -3.78995649e-01 ...,   9.12567986e-02
   -6.00944436e-01  -3.19677844e-01]
 [ -2.75451793e-01  -1.83886122e-01  -1.82939669e-01 ...,  -1.18157395e-01
   -1.55239559e-01  -3.45171201e-01]
 [  3.82012588e-02   7.94480420e-02  -4.73244566e-02 ...,   5.18017917e-02
    2.89973054e+00  -7.80901437e-02]]
Progress: 79.2% ... Training loss: 0.065 ... Validation loss: 0.146[[-0.16370104]
 [-0.95138318]
 [-1.1898449 ]
 [-0.7693151 ]
 [-0.06080716]
 [ 2.62248145]
 [-0.05198827]
 [-1.09692509]
 [-0.52815056]
 [ 1.0104502 ]
 [-0.09683289]
 [ 0.14186961]
 [-0.10323264]
 [-0.99719659]
 [-0.29908143]
 [ 0.86764066]
 [-0.83627273]
 [-0.79578138]
 [-0.62041441]
 [ 0.13749278]
 [-0.35427324]
 [ 4.4754541 ]
 [-0.94774072]
 [-1.64799032]
 [ 0.38371204]
 [-0.30951424]
 [ 4.29633224]
 [-1.90730296]]
[[ -1.88144544e-02  -3.06360333e-01   2.65816814e-01 ...,  -2.32446342e-01
   -3.41276179e-01   2.71141257e-01]
 [  5.82016846e-02   1.44413160e-01   8.21620725e-06 ...,  -2.22663477e-01
    1.59927359e+00   1.13615223e-01]
 [ -6.13681620e-02   2.57300770e-01   4.66638482e-01 ...,   2.34579944e-01
   -3.11335115e-01   9.65309910e-01]
 ..., 
 [ -1.83746129e-01  -2.35349706e-01  -3.78502112e-01 ...,   9.15958346e-02
   -6.02851027e-01  -3.18314776e-01]
 [ -2.75480220e-01  -1.84046566e-01  -1.83032292e-01 ...,  -1.18208359e-01
   -1.54715982e-01  -3.45506948e-01]
 [  3.85449736e-02   8.14942678e-02  -4.51392164e-02 ...,   5.24491162e-02
    2.89942732e+00  -7.56891488e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16054034]
 [-0.94870247]
 [-1.18802575]
 [-0.76597359]
 [-0.05783824]
 [ 2.62283739]
 [-0.04906501]
 [-1.09325976]
 [-0.52555337]
 [ 1.01307594]
 [-0.0941304 ]
 [ 0.14523168]
 [-0.10032865]
 [-0.99564472]
 [-0.29600857]
 [ 0.87105332]
 [-0.8330749 ]
 [-0.79352502]
 [-0.6182603 ]
 [ 0.1405996 ]
 [-0.35101356]
 [ 4.47568356]
 [-0.94574099]
 [-1.64414503]
 [ 0.38585133]
 [-0.30675845]
 [ 4.30095916]
 [-1.90686647]]
[[ -1.87890838e-02  -3.06141575e-01   2.65846693e-01 ...,  -2.32394746e-01
   -3.39407145e-01   2.71580162e-01]
 [  5.82252418e-02   1.44550273e-01   1.45786029e-04 ...,  -2.22619067e-01
    1.59912716e+00   1.13699881e-01]
 [ -6.12657599e-02   2.57964826e-01   4.67032338e-01 ...,   2.34764206e-01
   -3.11616913e-01   9.65832025e-01]
 ..., 
 [ -1.83756489e-01  -2.35454684e-01  -3.78357953e-01 ...,   9.15717648e-02
   -6.03233236e-01  -3.18269894e-01]
 [ -2.75581345e-01  -1.84537054e-01  -1.83698137e-01 ...,  -1.18385497e-01
   -1.52572459e-01  -3.46251558e-01]
 [  3.85122200e-02   8.12792293e-02  -4.52437104e-02 ...,   5.23881041e-02
    2.89944679e+00  -7.57765870e-02]]
Progress: 79.2% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16342759]
 [-0.95158766]
 [-1.19100716]
 [-0.76857101]
 [-0.06088792]
 [ 2.62189279]
 [-0.05192632]
 [-1.09675893]
 [-0.52818636]
 [ 1.0102555 ]
 [-0.09676678]
 [ 0.14161179]
 [-0.10404275]
 [-0.99736444]
 [-0.29916663]
 [ 0.86664019]
 [-0.83617179]
 [-0.79624672]
 [-0.62161444]
 [ 0.13752089]
 [-0.35452256]
 [ 4.47488594]
 [-0.94767842]
 [-1.64803065]
 [ 0.38362427]
 [-0.30951168]
 [ 4.29653968]
 [-1.90736813]]
[[ -1.86394832e-02  -3.05341993e-01   2.66424822e-01 ...,  -2.32127105e-01
   -3.43214014e-01   2.72519494e-01]
 [  5.82189987e-02   1.44513504e-01   1.49445008e-04 ...,  -2.22630462e-01
    1.59914744e+00   1.13631260e-01]
 [ -6.13368320e-02   2.57576372e-01   4.66890520e-01 ...,   2.34633461e-01
   -3.11590994e-01   9.65137791e-01]
 ..., 
 [ -1.83649144e-01  -2.34860786e-01  -3.77773520e-01 ...,   9.17731697e-02
   -6.04825381e-01  -3.18022752e-01]
 [ -2.75543886e-01  -1.84340692e-01  -1.83606557e-01 ...,  -1.18315168e-01
   -1.53345844e-01  -3.45959823e-01]
 [  3.84722686e-02   8.10357927e-02  -4.55398407e-02 ...,   5.23129994e-02
    2.89964500e+00  -7.63464562e-02]]
Progress: 79.2% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.15845872]
 [-0.94734219]
 [-1.18743864]
 [-0.76356333]
 [-0.0564192 ]
 [ 2.62362588]
 [-0.04741234]
 [-1.09194586]
 [-0.52363541]
 [ 1.01344134]
 [-0.09171581]
 [ 0.14616011]
 [-0.09943615]
 [-0.99477605]
 [-0.29408731]
 [ 0.87233095]
 [-0.83142185]
 [-0.79288872]
 [-0.61687751]
 [ 0.14208483]
 [-0.34967055]
 [ 4.47635585]
 [-0.94370235]
 [-1.6431612 ]
 [ 0.38701655]
 [-0.30503216]
 [ 4.30394199]
 [-1.90580297]]
[[ -1.88770572e-02  -3.06677631e-01   2.65379984e-01 ...,  -2.32566432e-01
   -3.40019642e-01   2.71030750e-01]
 [  5.82611689e-02   1.44749530e-01   3.13812420e-04 ...,  -2.22551563e-01
    1.59871693e+00   1.14039481e-01]
 [ -6.13340141e-02   2.57534168e-01   4.66529449e-01 ...,   2.34621551e-01
   -3.11996606e-01   9.64139547e-01]
 ..., 
 [ -1.83765493e-01  -2.35490457e-01  -3.78402073e-01 ...,   9.15684664e-02
   -6.02946785e-01  -3.18823546e-01]
 [ -2.75602575e-01  -1.84635963e-01  -1.83798152e-01 ...,  -1.18434110e-01
   -1.52237321e-01  -3.46266778e-01]
 [  3.84663831e-02   8.10090823e-02  -4.56042199e-02 ...,   5.22973764e-02
    2.89960417e+00  -7.62583369e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16224854]
 [-0.95113685]
 [-1.19058405]
 [-0.76680326]
 [-0.05980048]
 [ 2.62153385]
 [-0.05078793]
 [-1.09408104]
 [-0.52751481]
 [ 1.01137515]
 [-0.09526712]
 [ 0.14290927]
 [-0.1033885 ]
 [-0.99764706]
 [-0.29793115]
 [ 0.86822051]
 [-0.83529745]
 [-0.79578245]
 [-0.62006687]
 [ 0.13875774]
 [-0.3529317 ]
 [ 4.47526019]
 [-0.94654613]
 [-1.64615212]
 [ 0.38425028]
 [-0.30873027]
 [ 4.29776556]
 [-1.90786514]]
[[ -1.87019493e-02  -3.05645728e-01   2.66304070e-01 ...,  -2.32255070e-01
   -3.43580419e-01   2.72678671e-01]
 [  5.83323444e-02   1.45183820e-01   7.43893243e-04 ...,  -2.22412974e-01
    1.59766779e+00   1.14884861e-01]
 [ -6.11832886e-02   2.58441255e-01   4.67829978e-01 ...,   2.34932787e-01
   -3.14647820e-01   9.66350666e-01]
 ..., 
 [ -1.83771669e-01  -2.35556136e-01  -3.78444500e-01 ...,   9.15553074e-02
   -6.03293729e-01  -3.19007812e-01]
 [ -2.75582917e-01  -1.84526319e-01  -1.83693116e-01 ...,  -1.18401123e-01
   -1.52022076e-01  -3.46322691e-01]
 [  3.85414629e-02   8.14947163e-02  -4.52352768e-02 ...,   5.24314436e-02
    2.89951869e+00  -7.56051168e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.15820767]
 [-0.94793986]
 [-1.187575  ]
 [-0.76383101]
 [-0.05664027]
 [ 2.62402536]
 [-0.04769846]
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 [ 1.01342457]
 [-0.09194542]
 [ 0.14623001]
 [-0.09933697]
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 [-0.29401492]
 [ 0.87222353]
 [-0.83141543]
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 [ 0.14221606]
 [-0.3498485 ]
 [ 4.47575475]
 [-0.94367088]
 [-1.64355719]
 [ 0.38744092]
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 [ 4.30358798]
 [-1.90550518]]
[[ -1.88468771e-02  -3.06387610e-01   2.65437450e-01 ...,  -2.32499860e-01
   -3.40592800e-01   2.71723829e-01]
 [  5.83076579e-02   1.45059937e-01   5.95025038e-04 ...,  -2.22456630e-01
    1.59806245e+00   1.14770140e-01]
 [ -6.13912336e-02   2.57155864e-01   4.66671227e-01 ...,   2.34545091e-01
   -3.11145445e-01   9.63484900e-01]
 ..., 
 [ -1.83808984e-01  -2.35755032e-01  -3.78692588e-01 ...,   9.14935166e-02
   -6.02113512e-01  -3.19559485e-01]
 [ -2.75642590e-01  -1.84868849e-01  -1.83971871e-01 ...,  -1.18518283e-01
   -1.51437522e-01  -3.46639993e-01]
 [  3.84421988e-02   8.09397971e-02  -4.57442230e-02 ...,   5.22553270e-02
    2.89964129e+00  -7.66024119e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16452144]
 [-0.95456934]
 [-1.19283938]
 [-0.76880408]
 [-0.0613288 ]
 [ 2.61967234]
 [-0.05361084]
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 [ 1.00946866]
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 [ 0.14048197]
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 [ 0.86533242]
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 [ 0.13695032]
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 [ 4.47387098]
 [-0.94886967]
 [-1.64747068]
 [ 0.38221477]
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 [ 4.29267823]
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[[ -1.85693491e-02  -3.04765418e-01   2.67148846e-01 ...,  -2.31962183e-01
   -3.44453689e-01   2.74103676e-01]
 [  5.83238387e-02   1.45142113e-01   5.08642853e-04 ...,  -2.22418499e-01
    1.59852464e+00   1.14921749e-01]
 [ -6.10082368e-02   2.59359750e-01   4.69491998e-01 ...,   2.35299150e-01
   -3.13155215e-01   9.67768572e-01]
 ..., 
 [ -1.83730454e-01  -2.35304965e-01  -3.78382539e-01 ...,   9.16529061e-02
   -6.01420211e-01  -3.19063603e-01]
 [ -2.75506800e-01  -1.84068827e-01  -1.83124893e-01 ...,  -1.18269960e-01
   -1.52920619e-01  -3.45113813e-01]
 [  3.85078006e-02   8.13250542e-02  -4.52508740e-02 ...,   5.23802307e-02
    2.89940695e+00  -7.62098991e-02]]
Progress: 79.2% ... Training loss: 0.065 ... Validation loss: 0.137[[-0.15677074]
 [-0.94887135]
 [-1.18730066]
 [-0.76192498]
 [-0.05499146]
 [ 2.62318631]
 [-0.04738967]
 [-1.08986873]
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 [ 1.01342666]
 [-0.09096703]
 [ 0.14673711]
 [-0.09929979]
 [-0.99535457]
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 [ 0.87279001]
 [-0.83052334]
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 [ 0.14331209]
 [-0.34901634]
 [ 4.47538914]
 [-0.9420704 ]
 [-1.63999361]
 [ 0.38758463]
 [-0.30528441]
 [ 4.30418666]
 [-1.90641815]]
[[ -1.89424506e-02  -3.06770347e-01   2.65044608e-01 ...,  -2.32605057e-01
   -3.38657478e-01   2.70979661e-01]
 [  5.83231611e-02   1.45134411e-01   3.86949212e-04 ...,  -2.22419315e-01
    1.59856073e+00   1.14924224e-01]
 [ -6.10157906e-02   2.59222496e-01   4.68366810e-01 ...,   2.35295418e-01
   -3.12146888e-01   9.65148330e-01]
 ..., 
 [ -1.83761915e-01  -2.35459601e-01  -3.78515195e-01 ...,   9.15986133e-02
   -6.00897996e-01  -3.19009060e-01]
 [ -2.75631483e-01  -1.84748894e-01  -1.83869860e-01 ...,  -1.18482004e-01
   -1.51472389e-01  -3.46077317e-01]
 [  3.85177860e-02   8.13779285e-02  -4.52467211e-02 ...,   5.24018145e-02
    2.89938753e+00  -7.61081048e-02]]
Progress: 79.2% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.1611925 ]
 [-0.95230856]
 [-1.19076019]
 [-0.76484431]
 [-0.05829607]
 [ 2.62166446]
 [-0.05034542]
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 [ 1.010138  ]
 [-0.09451877]
 [ 0.14284933]
 [-0.10293768]
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 [ 0.86798155]
 [-0.83438461]
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 [ 0.13953451]
 [-0.35304007]
 [ 4.47461716]
 [-0.94499298]
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 [ 0.38452044]
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 [ 4.29774189]
 [-1.90770657]]
[[ -1.87532768e-02  -3.05716929e-01   2.65864861e-01 ...,  -2.32254700e-01
   -3.40103175e-01   2.72499359e-01]
 [  5.83341426e-02   1.45202918e-01   4.54975882e-04 ...,  -2.22399014e-01
    1.59855882e+00   1.14915146e-01]
 [ -6.10258240e-02   2.59264255e-01   4.68517889e-01 ...,   2.35282170e-01
   -3.12495021e-01   9.65922353e-01]
 ..., 
 [ -1.83715517e-01  -2.35203232e-01  -3.78228532e-01 ...,   9.16794139e-02
   -6.00791248e-01  -3.18906155e-01]
 [ -2.75672997e-01  -1.85008895e-01  -1.84254499e-01 ...,  -1.18566972e-01
   -1.51668834e-01  -3.46522535e-01]
 [  3.85772216e-02   8.17343842e-02  -4.48496942e-02 ...,   5.25186917e-02
    2.89928616e+00  -7.54980881e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16452049]
 [-0.95632821]
 [-1.19377552]
 [-0.7680998 ]
 [-0.06158984]
 [ 2.62013967]
 [-0.05351199]
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 [ 1.00885675]
 [-0.09755106]
 [ 0.13905045]
 [-0.10638556]
 [-0.99891626]
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 [ 0.86364864]
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 [ 0.13618563]
 [-0.35628942]
 [ 4.47393761]
 [-0.94644723]
 [-1.64762902]
 [ 0.3817315 ]
 [-0.31146556]
 [ 4.29057495]
 [-1.90898491]]
[[ -1.85662641e-02  -3.04618474e-01   2.67174327e-01 ...,  -2.31920712e-01
   -3.41085599e-01   2.73887446e-01]
 [  5.82763238e-02   1.44891762e-01   3.53381470e-04 ...,  -2.22493802e-01
    1.59892534e+00   1.14609036e-01]
 [ -6.09655947e-02   2.59589237e-01   4.68622284e-01 ...,   2.35379033e-01
   -3.10874873e-01   9.66008809e-01]
 ..., 
 [ -1.83732430e-01  -2.35304486e-01  -3.78528060e-01 ...,   9.16425687e-02
   -6.00279476e-01  -3.19023202e-01]
 [ -2.75611319e-01  -1.84701023e-01  -1.83970472e-01 ...,  -1.18458404e-01
   -1.52116142e-01  -3.46201749e-01]
 [  3.87404925e-02   8.26498006e-02  -4.38811265e-02 ...,   5.28218307e-02
    2.89908677e+00  -7.38495109e-02]]
Progress: 79.2% ... Training loss: 0.065 ... Validation loss: 0.138[[-0.15837609]
 [-0.9516585 ]
 [-1.19037929]
 [-0.76194765]
 [-0.05642733]
 [ 2.62117022]
 [-0.04811484]
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 [ 1.01358876]
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 [ 0.14409334]
 [-0.10054438]
 [-0.99529724]
 [-0.29632365]
 [ 0.86975655]
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 [ 0.14086111]
 [-0.35059863]
 [ 4.47427905]
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 [ 0.38556915]
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 [ 4.29894407]
 [-1.90750245]]
[[ -1.85850632e-02  -3.04673809e-01   2.67155755e-01 ...,  -2.31943028e-01
   -3.38796107e-01   2.74153644e-01]
 [  5.82558149e-02   1.44787983e-01   2.28841915e-04 ...,  -2.22527999e-01
    1.59921947e+00   1.14540280e-01]
 [ -6.09258661e-02   2.59788701e-01   4.68719591e-01 ...,   2.35453789e-01
   -3.09181607e-01   9.65263855e-01]
 ..., 
 [ -1.83962485e-01  -2.36568440e-01  -3.79880010e-01 ...,   9.12387656e-02
   -5.96349711e-01  -3.20923677e-01]
 [ -2.75599284e-01  -1.84614812e-01  -1.83881313e-01 ...,  -1.18434756e-01
   -1.51861993e-01  -3.46633959e-01]
 [  3.86793306e-02   8.23183281e-02  -4.41225302e-02 ...,   5.27028597e-02
    2.89900087e+00  -7.41552710e-02]]
Progress: 79.2% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.15996897]
 [-0.95224106]
 [-1.19096763]
 [-0.76386814]
 [-0.05806813]
 [ 2.62163145]
 [-0.04954324]
 [-1.09215779]
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 [ 1.01364371]
 [-0.09320424]
 [ 0.1435317 ]
 [-0.10172486]
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 [-0.29691647]
 [ 0.86933461]
 [-0.83315518]
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 [ 0.13991392]
 [-0.35076902]
 [ 4.47436945]
 [-0.94380229]
 [-1.64418265]
 [ 0.38476094]
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 [ 4.29671613]
 [-1.90860433]]
[[ -1.84934221e-02  -3.04202045e-01   2.67759047e-01 ...,  -2.31779397e-01
   -3.40364267e-01   2.74613751e-01]
 [  5.83038349e-02   1.45057068e-01   5.61457560e-04 ...,  -2.22438385e-01
    1.59911494e+00   1.15045511e-01]
 [ -6.10146550e-02   2.59308188e-01   4.68546370e-01 ...,   2.35285285e-01
   -3.08420098e-01   9.65590924e-01]
 ..., 
 [ -1.83940634e-01  -2.36472767e-01  -3.79840067e-01 ...,   9.12774515e-02
   -5.96743767e-01  -3.20815571e-01]
 [ -2.75524475e-01  -1.84190743e-01  -1.83500148e-01 ...,  -1.18298083e-01
   -1.52255452e-01  -3.46385784e-01]
 [  3.86038313e-02   8.18781223e-02  -4.47072682e-02 ...,   5.25626492e-02
    2.89917179e+00  -7.46814181e-02]]
Progress: 79.3% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15887241]
 [-0.95145347]
 [-1.18845092]
 [-0.76460987]
 [-0.05762962]
 [ 2.62266592]
 [-0.04881649]
 [-1.09326641]
 [-0.52445614]
 [ 1.01516148]
 [-0.0923838 ]
 [ 0.14473105]
 [-0.10038048]
 [-0.9959052 ]
 [-0.29540368]
 [ 0.87155602]
 [-0.83196308]
 [-0.79201928]
 [-0.61706352]
 [ 0.1410897 ]
 [-0.34904002]
 [ 4.47639423]
 [-0.94453793]
 [-1.64472073]
 [ 0.38605766]
 [-0.30549943]
 [ 4.2984018 ]
 [-1.9075024 ]]
[[ -1.86750458e-02  -3.05286718e-01   2.66231008e-01 ...,  -2.32091455e-01
   -3.37702218e-01   2.72466019e-01]
 [  5.83071797e-02   1.45080191e-01   5.68700114e-04 ...,  -2.22434001e-01
    1.59940253e+00   1.15007159e-01]
 [ -6.11417891e-02   2.58539589e-01   4.68004844e-01 ...,   2.35060439e-01
   -3.04963825e-01   9.64189979e-01]
 ..., 
 [ -1.83934660e-01  -2.36433884e-01  -3.79907955e-01 ...,   9.12938468e-02
   -5.97145332e-01  -3.21021776e-01]
 [ -2.75556795e-01  -1.84377176e-01  -1.83893870e-01 ...,  -1.18349733e-01
   -1.52320302e-01  -3.46856339e-01]
 [  3.85383379e-02   8.14975949e-02  -4.50878961e-02 ...,   5.24555191e-02
    2.89936545e+00  -7.51425256e-02]]
Progress: 79.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16099638]
 [-0.95324272]
 [-1.19060506]
 [-0.7652714 ]
 [-0.05815261]
 [ 2.62099306]
 [-0.04979183]
 [-1.09301755]
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 [ 1.01340785]
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 [ 0.14314726]
 [-0.1022252 ]
 [-0.99676392]
 [-0.29754538]
 [ 0.8696013 ]
 [-0.83447496]
 [-0.79464723]
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 [ 0.13918027]
 [-0.35096773]
 [ 4.47558382]
 [-0.94508625]
 [-1.64576921]
 [ 0.38504594]
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 [ 4.29593542]
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[[ -1.86059934e-02  -3.04839078e-01   2.66791107e-01 ...,  -2.31944642e-01
   -3.38521876e-01   2.73320884e-01]
 [  5.81795594e-02   1.44324574e-01  -3.36378278e-04 ...,  -2.22658330e-01
    1.60054695e+00   1.13634097e-01]
 [ -6.09588177e-02   2.59589590e-01   4.69109569e-01 ...,   2.35431251e-01
   -3.08276289e-01   9.65802301e-01]
 ..., 
 [ -1.83843730e-01  -2.35896178e-01  -3.79230111e-01 ...,   9.14610708e-02
   -5.98832135e-01  -3.20227868e-01]
 [ -2.75553412e-01  -1.84370811e-01  -1.83986065e-01 ...,  -1.18353422e-01
   -1.52603548e-01  -3.46799231e-01]
 [  3.85866229e-02   8.18062491e-02  -4.46028887e-02 ...,   5.25478889e-02
    2.89937364e+00  -7.45633521e-02]]
Progress: 79.3% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16097764]
 [-0.95326467]
 [-1.19080487]
 [-0.76489722]
 [-0.05812497]
 [ 2.62315404]
 [-0.04904546]
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 [ 1.01217906]
 [-0.09314415]
 [ 0.14322673]
 [-0.10146922]
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 [ 0.86971005]
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 [ 0.13926701]
 [-0.35158165]
 [ 4.47482132]
 [-0.9446494 ]
 [-1.64703347]
 [ 0.38548564]
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 [ 4.29619912]
 [-1.90798255]]
[[ -1.87563493e-02  -3.05675523e-01   2.65917958e-01 ...,  -2.32237788e-01
   -3.35940082e-01   2.71920327e-01]
 [  5.80992976e-02   1.43851155e-01  -8.34855727e-04 ...,  -2.22810366e-01
    1.60186187e+00   1.12903569e-01]
 [ -6.10936711e-02   2.58757526e-01   4.68185219e-01 ...,   2.35175622e-01
   -3.08251983e-01   9.64611297e-01]
 ..., 
 [ -1.83912031e-01  -2.36282342e-01  -3.79551478e-01 ...,   9.13418587e-02
   -5.97595491e-01  -3.20775487e-01]
 [ -2.75592007e-01  -1.84565244e-01  -1.84228062e-01 ...,  -1.18420669e-01
   -1.52184689e-01  -3.46892905e-01]
 [  3.86430959e-02   8.21445749e-02  -4.43802103e-02 ...,   5.26545354e-02
    2.89939927e+00  -7.42209290e-02]]
Progress: 79.3% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16141055]
 [-0.95376151]
 [-1.19146024]
 [-0.76518271]
 [-0.05929051]
 [ 2.62453546]
 [-0.04893623]
 [-1.09540185]
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 [ 1.01178296]
 [-0.09335319]
 [ 0.14191326]
 [-0.10211474]
 [-0.9942482 ]
 [-0.29892567]
 [ 0.86750211]
 [-0.83543912]
 [-0.79660025]
 [-0.62146886]
 [ 0.13831338]
 [-0.35315362]
 [ 4.47483105]
 [-0.94326129]
 [-1.64954522]
 [ 0.38525008]
 [-0.30641512]
 [ 4.29525867]
 [-1.90739926]]
[[ -1.86760829e-02  -3.05267052e-01   2.66635523e-01 ...,  -2.32090908e-01
   -3.37430845e-01   2.72312911e-01]
 [  5.80364162e-02   1.43512331e-01  -1.20015225e-03 ...,  -2.22914349e-01
    1.60286214e+00   1.12434188e-01]
 [ -6.13253865e-02   2.57436837e-01   4.66688151e-01 ...,   2.34766514e-01
   -3.04976235e-01   9.62940892e-01]
 ..., 
 [ -1.83878040e-01  -2.36115253e-01  -3.79417099e-01 ...,   9.14113690e-02
   -5.98633142e-01  -3.20628308e-01]
 [ -2.75572544e-01  -1.84463589e-01  -1.84017014e-01 ...,  -1.18393058e-01
   -1.52217718e-01  -3.46811115e-01]
 [  3.87102095e-02   8.24997422e-02  -4.39617432e-02 ...,   5.27813309e-02
    2.89936831e+00  -7.42894689e-02]]
Progress: 79.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16443848]
 [-0.9571299 ]
 [-1.19648936]
 [-0.76576634]
 [-0.06007169]
 [ 2.62188531]
 [-0.05115744]
 [-1.09512042]
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 [ 1.00893753]
 [-0.09560683]
 [ 0.13917863]
 [-0.1050968 ]
 [-0.9972677 ]
 [-0.30271831]
 [ 0.86360545]
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 [ 0.13563382]
 [-0.35680582]
 [ 4.47359787]
 [-0.94381918]
 [-1.65105701]
 [ 0.38201216]
 [-0.30907403]
 [ 4.28923388]
 [-1.90987111]]
[[ -1.85449164e-02  -3.04423450e-01   2.67806581e-01 ...,  -2.31857371e-01
   -3.38283881e-01   2.73559882e-01]
 [  5.79975033e-02   1.43304570e-01  -1.29154887e-03 ...,  -2.22983210e-01
    1.60325199e+00   1.12184278e-01]
 [ -6.09581035e-02   2.59582002e-01   4.68602656e-01 ...,   2.35449036e-01
   -3.07377757e-01   9.66333322e-01]
 ..., 
 [ -1.83910682e-01  -2.36301937e-01  -3.79626222e-01 ...,   9.13501771e-02
   -5.98137447e-01  -3.20904236e-01]
 [ -2.75512754e-01  -1.84123065e-01  -1.83586387e-01 ...,  -1.18288211e-01
   -1.52814155e-01  -3.46341652e-01]
 [  3.88617276e-02   8.33609580e-02  -4.29839062e-02 ...,   5.30684469e-02
    2.89895823e+00  -7.30191259e-02]]
Progress: 79.3% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.15742082]
 [-0.95035352]
 [-1.19054052]
 [-0.7602275 ]
 [-0.05418794]
 [ 2.62683644]
 [-0.04491181]
 [-1.09079725]
 [-0.52334853]
 [ 1.01342128]
 [-0.08904935]
 [ 0.14522858]
 [-0.09848285]
 [-0.99237127]
 [-0.29547722]
 [ 0.87114675]
 [-0.83244445]
 [-0.79638882]
 [-0.61868438]
 [ 0.14173116]
 [-0.3509563 ]
 [ 4.47593767]
 [-0.93908176]
 [-1.64527329]
 [ 0.38733626]
 [-0.30210211]
 [ 4.30115887]
 [-1.90592226]]
[[ -1.88631727e-02  -3.06223608e-01   2.65845138e-01 ...,  -2.32444340e-01
   -3.34533766e-01   2.70715528e-01]
 [  5.79707908e-02   1.43160751e-01  -1.39093409e-03 ...,  -2.23033111e-01
    1.60373130e+00   1.11905821e-01]
 [ -6.12925126e-02   2.57546241e-01   4.66229890e-01 ...,   2.34781035e-01
   -3.01680243e-01   9.61682989e-01]
 ..., 
 [ -1.84053861e-01  -2.37046146e-01  -3.80533465e-01 ...,   9.10990237e-02
   -5.96282364e-01  -3.21802223e-01]
 [ -2.75517165e-01  -1.84160739e-01  -1.83611303e-01 ...,  -1.18298049e-01
   -1.53198571e-01  -3.46408104e-01]
 [  3.87762742e-02   8.28825356e-02  -4.35540324e-02 ...,   5.29011961e-02
    2.89919105e+00  -7.39349076e-02]]
Progress: 79.3% ... Training loss: 0.065 ... Validation loss: 0.146[[-0.16283092]
 [-0.95511294]
 [-1.1934007 ]
 [-0.76473055]
 [-0.05844918]
 [ 2.62163105]
 [-0.05035549]
 [-1.09379051]
 [-0.52792756]
 [ 1.01118333]
 [-0.09308009]
 [ 0.14078349]
 [-0.10444318]
 [-0.99763556]
 [-0.30030039]
 [ 0.86593407]
 [-0.83717617]
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 [-0.62212326]
 [ 0.13737867]
 [-0.35513999]
 [ 4.47528946]
 [-0.9444772 ]
 [-1.64802512]
 [ 0.38253567]
 [-0.30697694]
 [ 4.29327356]
 [-1.90966305]]
[[ -1.86833623e-02  -3.05170572e-01   2.66687648e-01 ...,  -2.32111924e-01
   -3.36254224e-01   2.72614243e-01]
 [  5.79628738e-02   1.43116429e-01  -1.39010470e-03 ...,  -2.23047550e-01
    1.60381179e+00   1.11727113e-01]
 [ -6.09678753e-02   2.59491481e-01   4.68578366e-01 ...,   2.35398003e-01
   -3.05132458e-01   9.65631389e-01]
 ..., 
 [ -1.84018735e-01  -2.36836396e-01  -3.80403704e-01 ...,   9.11680474e-02
   -5.97079174e-01  -3.21382762e-01]
 [ -2.75544947e-01  -1.84389706e-01  -1.83806621e-01 ...,  -1.18361198e-01
   -1.53046471e-01  -3.46995680e-01]
 [  3.89589722e-02   8.39560135e-02  -4.24542337e-02 ...,   5.32418042e-02
    2.89883138e+00  -7.20159679e-02]]
Progress: 79.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.1602508 ]
 [-0.95337183]
 [-1.19077805]
 [-0.76433176]
 [-0.05850669]
 [ 2.62551071]
 [-0.04859457]
 [-1.09508436]
 [-0.52407384]
 [ 1.01294941]
 [-0.09154098]
 [ 0.14211994]
 [-0.10298565]
 [-0.99362477]
 [-0.29853882]
 [ 0.86775566]
 [-0.83518311]
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 [-0.61994302]
 [ 0.13896931]
 [-0.35340443]
 [ 4.47584569]
 [-0.94233503]
 [-1.64863814]
 [ 0.38524756]
 [-0.30557662]
 [ 4.29615127]
 [-1.90689247]]
[[ -1.88712814e-02  -3.06211666e-01   2.64949241e-01 ...,  -2.32452217e-01
   -3.31602977e-01   2.71015032e-01]
 [  5.80254968e-02   1.43477755e-01  -1.04027953e-03 ...,  -2.22928486e-01
    1.60269706e+00   1.12343985e-01]
 [ -6.14560200e-02   2.56653138e-01   4.65465968e-01 ...,   2.34497918e-01
   -2.99012797e-01   9.61056664e-01]
 ..., 
 [ -1.84110187e-01  -2.37362292e-01  -3.81005129e-01 ...,   9.09998141e-02
   -5.95295596e-01  -3.22160392e-01]
 [ -2.75560285e-01  -1.84479571e-01  -1.84146374e-01 ...,  -1.18410641e-01
   -1.50454553e-01  -3.47065111e-01]
 [  3.90708026e-02   8.46330333e-02  -4.21269380e-02 ...,   5.34417858e-02
    2.89874607e+00  -7.13213823e-02]]
Progress: 79.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16419357]
 [-0.95648039]
 [-1.19445767]
 [-0.76550542]
 [-0.06045967]
 [ 2.62168882]
 [-0.05221   ]
 [-1.09551622]
 [-0.52736323]
 [ 1.01138415]
 [-0.09471204]
 [ 0.1387531 ]
 [-0.10632594]
 [-0.99725466]
 [-0.30230265]
 [ 0.86376499]
 [-0.83890068]
 [-0.80151421]
 [-0.62332119]
 [ 0.13597403]
 [-0.35641627]
 [ 4.47437858]
 [-0.94498749]
 [-1.65077929]
 [ 0.3809663 ]
 [-0.3080568 ]
 [ 4.28910669]
 [-1.90930184]]
[[ -1.85319144e-02  -3.04315607e-01   2.67430520e-01 ...,  -2.31859463e-01
   -3.34215607e-01   2.73612585e-01]
 [  5.81210850e-02   1.44003800e-01  -4.78268024e-04 ...,  -2.22754960e-01
    1.60215268e+00   1.13219173e-01]
 [ -6.11680354e-02   2.58321830e-01   4.67416869e-01 ...,   2.35040011e-01
   -3.00607223e-01   9.63825408e-01]
 ..., 
 [ -1.84143588e-01  -2.37566392e-01  -3.81256723e-01 ...,   9.09435075e-02
   -5.94717962e-01  -3.22455607e-01]
 [ -2.75561981e-01  -1.84488617e-01  -1.84100265e-01 ...,  -1.18418516e-01
   -1.50302302e-01  -3.47120897e-01]
 [  3.90851551e-02   8.47098819e-02  -4.19392595e-02 ...,   5.34641048e-02
    2.89868083e+00  -7.11983469e-02]]
Progress: 79.3% ... Training loss: 0.064 ... Validation loss: 0.139[[-0.15972818]
 [-0.95262861]
 [-1.19215134]
 [-0.76111961]
 [-0.05668669]
 [ 2.62462801]
 [-0.04782503]
 [-1.09174802]
 [-0.52390666]
 [ 1.01327267]
 [-0.09064484]
 [ 0.14258841]
 [-0.10176509]
 [-0.99439016]
 [-0.29802218]
 [ 0.86813075]
 [-0.8348247 ]
 [-0.79876659]
 [-0.62094373]
 [ 0.13974225]
 [-0.35345859]
 [ 4.47497166]
 [-0.94100277]
 [-1.64731448]
 [ 0.38391971]
 [-0.30368022]
 [ 4.29545697]
 [-1.90704336]]
[[ -1.86524286e-02  -3.04962279e-01   2.66790985e-01 ...,  -2.32094670e-01
   -3.31788987e-01   2.72928660e-01]
 [  5.81813219e-02   1.44296497e-01  -1.85464868e-04 ...,  -2.22641913e-01
    1.60194391e+00   1.13852258e-01]
 [ -6.12548936e-02   2.57711936e-01   4.66061019e-01 ...,   2.34866930e-01
   -2.95064765e-01   9.62326062e-01]
 ..., 
 [ -1.84201887e-01  -2.37889440e-01  -3.81574430e-01 ...,   9.08367967e-02
   -5.93985814e-01  -3.23010277e-01]
 [ -2.75656090e-01  -1.85033137e-01  -1.84653099e-01 ...,  -1.18596438e-01
   -1.47770407e-01  -3.47996132e-01]
 [  3.89166452e-02   8.37431958e-02  -4.25449183e-02 ...,   5.31489275e-02
    2.89878602e+00  -7.23535392e-02]]
Progress: 79.3% ... Training loss: 0.063 ... Validation loss: 0.142[[-0.15996632]
 [-0.95334997]
 [-1.19198751]
 [-0.76134744]
 [-0.05768249]
 [ 2.62285622]
 [-0.04906681]
 [-1.09238124]
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 [ 1.01269114]
 [-0.09171138]
 [ 0.14183057]
 [-0.10328767]
 [-0.99553907]
 [-0.29908425]
 [ 0.86688337]
 [-0.83532134]
 [-0.79850706]
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 [ 0.13882927]
 [-0.35406393]
 [ 4.47384155]
 [-0.94104022]
 [-1.64617952]
 [ 0.38299789]
 [-0.30538766]
 [ 4.29544037]
 [-1.90704286]]
[[ -1.85116798e-02  -3.04089452e-01   2.67338546e-01 ...,  -2.31807114e-01
   -3.35412663e-01   2.74190861e-01]
 [  5.81562252e-02   1.44162663e-01  -3.19366227e-04 ...,  -2.22682604e-01
    1.60229332e+00   1.13653319e-01]
 [ -6.11589055e-02   2.58191781e-01   4.66598540e-01 ...,   2.35027310e-01
   -2.98095423e-01   9.62523277e-01]
 ..., 
 [ -1.84144260e-01  -2.37571827e-01  -3.81153945e-01 ...,   9.09436235e-02
   -5.94917972e-01  -3.22749484e-01]
 [ -2.75727048e-01  -1.85426029e-01  -1.84923307e-01 ...,  -1.18720641e-01
   -1.46712626e-01  -3.48737582e-01]
 [  3.88859084e-02   8.35525030e-02  -4.27454304e-02 ...,   5.30913810e-02
    2.89883557e+00  -7.25357885e-02]]
Progress: 79.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15754192]
 [-0.95103911]
 [-1.18874165]
 [-0.760308  ]
 [-0.05697971]
 [ 2.623933  ]
 [-0.04761637]
 [-1.09173278]
 [-0.52187261]
 [ 1.01538433]
 [-0.09010104]
 [ 0.1436601 ]
 [-0.10124871]
 [-0.99359113]
 [-0.29685716]
 [ 0.86889438]
 [-0.83226622]
 [-0.79471331]
 [-0.61958345]
 [ 0.14058977]
 [-0.35182458]
 [ 4.47442694]
 [-0.93893633]
 [-1.64413569]
 [ 0.38452719]
 [-0.30369398]
 [ 4.29992716]
 [-1.9058482 ]]
[[ -1.85763085e-02  -3.04415331e-01   2.67132441e-01 ...,  -2.31928020e-01
   -3.34089684e-01   2.73558553e-01]
 [  5.81601360e-02   1.44184833e-01  -2.84287450e-04 ...,  -2.22675589e-01
    1.60226387e+00   1.13697955e-01]
 [ -6.12696017e-02   2.57552638e-01   4.65906178e-01 ...,   2.34817686e-01
   -2.98144823e-01   9.61327017e-01]
 ..., 
 [ -1.84170119e-01  -2.37729015e-01  -3.81336187e-01 ...,   9.08955385e-02
   -5.94694763e-01  -3.23174373e-01]
 [ -2.75709703e-01  -1.85308758e-01  -1.84986661e-01 ...,  -1.18682081e-01
   -1.46784628e-01  -3.48636315e-01]
 [  3.88293584e-02   8.32245418e-02  -4.30831895e-02 ...,   5.29858106e-02
    2.89885525e+00  -7.27451593e-02]]
Progress: 79.3% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16401552]
 [-0.95717477]
 [-1.19285558]
 [-0.76639457]
 [-0.06288672]
 [ 2.62176473]
 [-0.05307312]
 [-1.09758567]
 [-0.52759155]
 [ 1.01067895]
 [-0.09526398]
 [ 0.13758372]
 [-0.10845262]
 [-0.99775789]
 [-0.3032235 ]
 [ 0.86210127]
 [-0.83881505]
 [-0.79963595]
 [-0.62421887]
 [ 0.13405644]
 [-0.35755273]
 [ 4.47162432]
 [-0.94477716]
 [-1.65096863]
 [ 0.38031165]
 [-0.31061185]
 [ 4.28937411]
 [-1.90870735]]
[[ -1.83174864e-02  -3.02929441e-01   2.68614979e-01 ...,  -2.31432666e-01
   -3.38977142e-01   2.75231502e-01]
 [  5.80552545e-02   1.43537473e-01  -1.05348887e-03 ...,  -2.22862716e-01
    1.60315076e+00   1.12458050e-01]
 [ -6.12262243e-02   2.57924406e-01   4.66639288e-01 ...,   2.34955963e-01
   -3.01675683e-01   9.62627602e-01]
 ..., 
 [ -1.83935685e-01  -2.36381792e-01  -3.79825983e-01 ...,   9.13272142e-02
   -5.96549361e-01  -3.21410831e-01]
 [ -2.75627720e-01  -1.84821055e-01  -1.84364770e-01 ...,  -1.18512939e-01
   -1.48165869e-01  -3.47880504e-01]
 [  3.88456272e-02   8.33415836e-02  -4.29274172e-02 ...,   5.30090413e-02
    2.89900049e+00  -7.29494288e-02]]
Progress: 79.3% ... Training loss: 0.065 ... Validation loss: 0.138[[-0.15594609]
 [-0.95181502]
 [-1.18807619]
 [-0.75992891]
 [-0.05747637]
 [ 2.62433274]
 [-0.04662798]
 [-1.09211841]
 [-0.52232597]
 [ 1.01538827]
 [-0.08915562]
 [ 0.14423547]
 [-0.09994335]
 [-0.99174189]
 [-0.29726067]
 [ 0.86864398]
 [-0.83146742]
 [-0.79211352]
 [-0.61987022]
 [ 0.14076664]
 [-0.34982615]
 [ 4.47415299]
 [-0.93623202]
 [-1.64275296]
 [ 0.38579744]
 [-0.3056946 ]
 [ 4.30237659]
 [-1.90562321]]
[[ -1.87528902e-02  -3.05331957e-01   2.66550322e-01 ...,  -2.32174896e-01
   -3.35606583e-01   2.72223421e-01]
 [  5.80022227e-02   1.43231220e-01  -1.46043334e-03 ...,  -2.22964543e-01
    1.60337226e+00   1.11751882e-01]
 [ -6.11099344e-02   2.58458079e-01   4.66682865e-01 ...,   2.35146469e-01
   -3.03426265e-01   9.61412559e-01]
 ..., 
 [ -1.84021842e-01  -2.36843510e-01  -3.80308828e-01 ...,   9.11801634e-02
   -5.95161730e-01  -3.21916174e-01]
 [ -2.75636549e-01  -1.84876232e-01  -1.84546231e-01 ...,  -1.18511541e-01
   -1.49045600e-01  -3.47931902e-01]
 [  3.87880805e-02   8.30179379e-02  -4.33089662e-02 ...,   5.29128367e-02
    2.89896880e+00  -7.30561496e-02]]
Progress: 79.3% ... Training loss: 0.064 ... Validation loss: 0.146[[-0.15680305]
 [-0.95248535]
 [-1.18945607]
 [-0.75973493]
 [-0.05740309]
 [ 2.62515228]
 [-0.04719817]
 [-1.09157451]
 [-0.52365162]
 [ 1.01347807]
 [-0.08996709]
 [ 0.14413372]
 [-0.10023688]
 [-0.99224097]
 [-0.2980037 ]
 [ 0.86836508]
 [-0.83262455]
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 [-0.62097258]
 [ 0.14045576]
 [-0.34996424]
 [ 4.47388425]
 [-0.93703145]
 [-1.64374024]
 [ 0.38569501]
 [-0.30652533]
 [ 4.30164593]
 [-1.90628531]]
[[ -1.88819187e-02  -3.06190679e-01   2.65874283e-01 ...,  -2.32417510e-01
   -3.34879814e-01   2.71001844e-01]
 [  5.79125149e-02   1.42677203e-01  -2.06732836e-03 ...,  -2.23126562e-01
    1.60402690e+00   1.10691733e-01]
 [ -6.10272364e-02   2.58952227e-01   4.67422310e-01 ...,   2.35346822e-01
   -3.04991356e-01   9.61135289e-01]
 ..., 
 [ -1.83999045e-01  -2.36734212e-01  -3.80181402e-01 ...,   9.12288765e-02
   -5.95558347e-01  -3.21724459e-01]
 [ -2.75631640e-01  -1.84859159e-01  -1.84715329e-01 ...,  -1.18505049e-01
   -1.48916803e-01  -3.48161584e-01]
 [  3.88135618e-02   8.31734022e-02  -4.29008984e-02 ...,   5.29637469e-02
    2.89891096e+00  -7.31452918e-02]]
Progress: 79.4% ... Training loss: 0.063 ... Validation loss: 0.146[[-0.15906679]
 [-0.9537135 ]
 [-1.19212278]
 [-0.76142041]
 [-0.05816323]
 [ 2.62395906]
 [-0.04882402]
 [-1.09188543]
 [-0.5264349 ]
 [ 1.01133227]
 [-0.09093335]
 [ 0.14248458]
 [-0.10198721]
 [-0.99456572]
 [-0.29959648]
 [ 0.86599035]
 [-0.83508922]
 [-0.79649227]
 [-0.62273428]
 [ 0.13892448]
 [-0.35217186]
 [ 4.47424163]
 [-0.93844051]
 [-1.64444787]
 [ 0.38401242]
 [-0.3085511 ]
 [ 4.29938866]
 [-1.90802148]]
[[ -1.88873221e-02  -3.06270897e-01   2.66144930e-01 ...,  -2.32436860e-01
   -3.36380040e-01   2.71490685e-01]
 [  5.78638446e-02   1.42429281e-01  -2.40886363e-03 ...,  -2.23208262e-01
    1.60474651e+00   1.10488762e-01]
 [ -6.07985793e-02   2.60294750e-01   4.68553430e-01 ...,   2.35768671e-01
   -3.09767820e-01   9.62996961e-01]
 ..., 
 [ -1.83925819e-01  -2.36338584e-01  -3.79689707e-01 ...,   9.13685383e-02
   -5.96701847e-01  -3.21397496e-01]
 [ -2.75572553e-01  -1.84525883e-01  -1.84403950e-01 ...,  -1.18406860e-01
   -1.49437105e-01  -3.47374083e-01]
 [  3.87708900e-02   8.29193731e-02  -4.30380423e-02 ...,   5.28727740e-02
    2.89892921e+00  -7.34292499e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16119452]
 [-0.95514414]
 [-1.19340338]
 [-0.76351117]
 [-0.0599633 ]
 [ 2.62334492]
 [-0.05038733]
 [-1.09426889]
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 [ 1.01075175]
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 [ 0.14046968]
 [-0.10417476]
 [-0.99529399]
 [-0.30128838]
 [ 0.86419348]
 [-0.83698933]
 [-0.79802455]
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 [ 0.13704477]
 [-0.35375783]
 [ 4.47435743]
 [-0.94118149]
 [-1.6474101 ]
 [ 0.38291263]
 [-0.30992745]
 [ 4.2959879 ]
 [-1.90811141]]
[[ -1.87914555e-02  -3.05701407e-01   2.66566742e-01 ...,  -2.32251107e-01
   -3.36378834e-01   2.71852466e-01]
 [  5.78623003e-02   1.42425193e-01  -2.44986998e-03 ...,  -2.23209761e-01
    1.60483905e+00   1.10465896e-01]
 [ -6.09674603e-02   2.59321847e-01   4.67621155e-01 ...,   2.35457616e-01
   -3.06971568e-01   9.62125714e-01]
 ..., 
 [ -1.83852570e-01  -2.35932158e-01  -3.79351500e-01 ...,   9.15062752e-02
   -5.98623050e-01  -3.21021818e-01]
 [ -2.75584680e-01  -1.84613023e-01  -1.84418343e-01 ...,  -1.18436462e-01
   -1.48716768e-01  -3.47665167e-01]
 [  3.88919797e-02   8.36343747e-02  -4.24676808e-02 ...,   5.31003377e-02
    2.89883653e+00  -7.28701471e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15768626]
 [-0.9519256 ]
 [-1.18949292]
 [-0.76139457]
 [-0.05771446]
 [ 2.62568653]
 [-0.04764646]
 [-1.09305571]
 [-0.52315825]
 [ 1.01360231]
 [-0.08994608]
 [ 0.14366544]
 [-0.10097858]
 [-0.99214752]
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 [ 0.86798547]
 [-0.83356412]
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 [ 0.14013519]
 [-0.35102097]
 [ 4.47571684]
 [-0.93879348]
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 [ 0.38546496]
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 [ 4.30092809]
 [-1.90611683]]
[[ -1.89587994e-02  -3.06663131e-01   2.65473627e-01 ...,  -2.32564913e-01
   -3.32913593e-01   2.70389199e-01]
 [  5.78452160e-02   1.42325052e-01  -2.49838059e-03 ...,  -2.23241548e-01
    1.60486021e+00   1.10348901e-01]
 [ -6.11712389e-02   2.58130370e-01   4.66085314e-01 ...,   2.35087858e-01
   -3.03454058e-01   9.59792445e-01]
 ..., 
 [ -1.83940284e-01  -2.36421647e-01  -3.79936771e-01 ...,   9.13460543e-02
   -5.97133007e-01  -3.21984584e-01]
 [ -2.75616782e-01  -1.84808578e-01  -1.84526356e-01 ...,  -1.18494252e-01
   -1.48351338e-01  -3.48006389e-01]
 [  3.88716580e-02   8.35350227e-02  -4.25123925e-02 ...,   5.30643399e-02
    2.89900247e+00  -7.29201170e-02]]
Progress: 79.4% ... Training loss: 0.063 ... Validation loss: 0.145[[-0.16145345]
 [-0.95525209]
 [-1.1910091 ]
 [-0.76611294]
 [-0.06110853]
 [ 2.62210133]
 [-0.05124916]
 [-1.09620713]
 [-0.52613118]
 [ 1.01360482]
 [-0.09298503]
 [ 0.14074923]
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 [ 4.47569314]
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 [ 0.38236355]
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 [ 4.29447915]
 [-1.90867528]]
[[ -1.87994737e-02  -3.05717385e-01   2.66120481e-01 ...,  -2.32248154e-01
   -3.33429724e-01   2.72325742e-01]
 [  5.78565060e-02   1.42386529e-01  -2.43028289e-03 ...,  -2.23215888e-01
    1.60457778e+00   1.10541207e-01]
 [ -6.10139658e-02   2.59080947e-01   4.67145483e-01 ...,   2.35381600e-01
   -3.03625866e-01   9.62489193e-01]
 ..., 
 [ -1.83983625e-01  -2.36678113e-01  -3.80218187e-01 ...,   9.12713581e-02
   -5.96603204e-01  -3.22252052e-01]
 [ -2.75632538e-01  -1.84897080e-01  -1.84715104e-01 ...,  -1.18517343e-01
   -1.48485344e-01  -3.48132299e-01]
 [  3.88521239e-02   8.34264392e-02  -4.26683433e-02 ...,   5.30280264e-02
    2.89897995e+00  -7.28963785e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16107569]
 [-0.95477106]
 [-1.1904121 ]
 [-0.76529485]
 [-0.05970761]
 [ 2.62062671]
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 [ 1.01398122]
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 [ 0.86606253]
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 [ 4.47491273]
 [-0.94326159]
 [-1.64452891]
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 [ 4.29510795]
 [-1.90981352]]
[[ -1.87725576e-02  -3.05617112e-01   2.66223883e-01 ...,  -2.32207879e-01
   -3.34068566e-01   2.72732743e-01]
 [  5.77909444e-02   1.41995420e-01  -2.84449956e-03 ...,  -2.23339660e-01
    1.60534102e+00   1.09884283e-01]
 [ -6.07351944e-02   2.60571385e-01   4.68622484e-01 ...,   2.35908946e-01
   -3.05003307e-01   9.64404034e-01]
 ..., 
 [ -1.83952156e-01  -2.36484394e-01  -3.80123622e-01 ...,   9.13289495e-02
   -5.97179474e-01  -3.21963778e-01]
 [ -2.75489216e-01  -1.84090409e-01  -1.83741677e-01 ...,  -1.18250245e-01
   -1.49772760e-01  -3.47230578e-01]
 [  3.88420247e-02   8.33577833e-02  -4.26447108e-02 ...,   5.30038633e-02
    2.89893051e+00  -7.31337513e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16261904]
 [-0.95662004]
 [-1.19238152]
 [-0.76605651]
 [-0.06069105]
 [ 2.62103563]
 [-0.05195212]
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 [ 1.01192855]
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 [ 0.13975041]
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 [ 0.13584287]
 [-0.3554327 ]
 [ 4.47507336]
 [-0.94296451]
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 [ 0.38058125]
 [-0.31041389]
 [ 4.2920194 ]
 [-1.91059979]]
[[ -1.88886249e-02  -3.06284616e-01   2.65482375e-01 ...,  -2.32443930e-01
   -3.32408974e-01   2.71627155e-01]
 [  5.78149668e-02   1.42130082e-01  -2.67632754e-03 ...,  -2.23298854e-01
    1.60527189e+00   1.10126985e-01]
 [ -6.06370108e-02   2.61132167e-01   4.69156067e-01 ...,   2.36112535e-01
   -3.02148851e-01   9.64706456e-01]
 ..., 
 [ -1.83973709e-01  -2.36623585e-01  -3.80351765e-01 ...,   9.12995315e-02
   -5.96707299e-01  -3.22403910e-01]
 [ -2.75479370e-01  -1.84062341e-01  -1.83962950e-01 ...,  -1.18249280e-01
   -1.48422692e-01  -3.47531672e-01]
 [  3.88581953e-02   8.34575458e-02  -4.25125788e-02 ...,   5.30243530e-02
    2.89903996e+00  -7.29983047e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16099152]
 [-0.95545876]
 [-1.19156115]
 [-0.7649081 ]
 [-0.05936441]
 [ 2.62085077]
 [-0.050936  ]
 [-1.09211125]
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 [ 1.0131862 ]
 [-0.09239026]
 [ 0.14151567]
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 [-0.99761992]
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 [ 0.86595488]
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 [ 0.13747691]
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 [ 4.47341042]
 [-0.94255888]
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 [ 0.38146232]
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 [ 4.29493629]
 [-1.91145569]]
[[ -1.88211227e-02  -3.05826604e-01   2.66137841e-01 ...,  -2.32344181e-01
   -3.33082342e-01   2.72673542e-01]
 [  5.78970902e-02   1.42661540e-01  -2.27199487e-03 ...,  -2.23154930e-01
    1.60488074e+00   1.11202977e-01]
 [ -6.04391258e-02   2.62332053e-01   4.70736680e-01 ...,   2.36458247e-01
   -3.05943023e-01   9.66185567e-01]
 ..., 
 [ -1.83955118e-01  -2.36518722e-01  -3.80302221e-01 ...,   9.13343757e-02
   -5.96942648e-01  -3.22185468e-01]
 [ -2.75515131e-01  -1.84239650e-01  -1.84077596e-01 ...,  -1.18303691e-01
   -1.47700482e-01  -3.47514746e-01]
 [  3.87972303e-02   8.30933951e-02  -4.29839077e-02 ...,   5.29123146e-02
    2.89903955e+00  -7.32497957e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15626559]
 [-0.95006112]
 [-1.18801481]
 [-0.76168156]
 [-0.0551551 ]
 [ 2.62474308]
 [-0.04569179]
 [-1.08991103]
 [-0.52260199]
 [ 1.01640849]
 [-0.08751884]
 [ 0.14601565]
 [-0.09789692]
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 [ 0.14186371]
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 [ 4.47637066]
 [-0.93898516]
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 [ 0.38579075]
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 [ 4.30275776]
 [-1.90847589]]
[[-0.01905686 -0.30716781  0.26429748 ..., -0.23275816 -0.32930845
   0.27044484]
 [ 0.05773648  0.14171465 -0.00344874 ..., -0.22343987  1.60602278
   0.10964191]
 [-0.06077888  0.26038744  0.46822221 ...,  0.23583269 -0.29881341
   0.9619918 ]
 ..., 
 [-0.18404869 -0.23704781 -0.38078026 ...,  0.09116103 -0.59534983
  -0.32288733]
 [-0.27552929 -0.18435501 -0.1841793  ..., -0.11833858 -0.14783568
  -0.34740426]
 [ 0.03878085  0.08303187 -0.04321068 ...,  0.05288369  2.89903712
  -0.07340488]]
Progress: 79.4% ... Training loss: 0.065 ... Validation loss: 0.149[[-0.1585982 ]
 [-0.95109965]
 [-1.18798283]
 [-0.76465375]
 [-0.05676666]
 [ 2.62566341]
 [-0.04775438]
 [-1.09220858]
 [-0.52440789]
 [ 1.01615305]
 [-0.08911074]
 [ 0.14509143]
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 [ 0.38508941]
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 [ 4.30034335]
 [-1.91022259]]
[[-0.01903329 -0.30715636  0.26505806 ..., -0.23275975 -0.33088641
   0.27148679]
 [ 0.05776981  0.14191692 -0.00332958 ..., -0.22338159  1.60584619
   0.10980743]
 [-0.06088822  0.25987677  0.46885959 ...,  0.23562266 -0.30106265
   0.96314091]
 ..., 
 [-0.1839156  -0.2362936  -0.37997336 ...,  0.09140041 -0.59722966
  -0.32198732]
 [-0.27542013 -0.18372264 -0.18310503 ..., -0.11814307 -0.14841762
  -0.3459077 ]
 [ 0.03870084  0.08253586 -0.04370746 ...,  0.05272007  2.8993913
  -0.07440376]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16345075]
 [-0.95472831]
 [-1.19009601]
 [-0.76987323]
 [-0.06123937]
 [ 2.62577543]
 [-0.051136  ]
 [-1.09708366]
 [-0.52749426]
 [ 1.01457756]
 [-0.09394376]
 [ 0.1413542 ]
 [-0.10361561]
 [-0.99650412]
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 [-0.83756738]
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 [ 4.47537813]
 [-0.9470297 ]
 [-1.64747005]
 [ 0.38270779]
 [-0.31002362]
 [ 4.29268541]
 [-1.91170986]]
[[-0.018954   -0.30670735  0.26575998 ..., -0.23262563 -0.33207127
   0.27227137]
 [ 0.05779693  0.14208601 -0.0031685  ..., -0.22333891  1.60643253
   0.11017263]
 [-0.0610442   0.25894397  0.46823653 ...,  0.23532166 -0.30026267
   0.96305484]
 ..., 
 [-0.18385662 -0.23598365 -0.37979708 ...,  0.09152022 -0.59774643
  -0.3217532 ]
 [-0.27534264 -0.18324097 -0.18249722 ..., -0.11798857 -0.15041294
  -0.3451983 ]
 [ 0.0388137   0.08318832 -0.04304955 ...,  0.05294179  2.89915931
  -0.07351742]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16310835]
 [-0.95454037]
 [-1.19102029]
 [-0.76887326]
 [-0.06013741]
 [ 2.62728877]
 [-0.05035304]
 [-1.09644481]
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 [ 1.01325701]
 [-0.09387597]
 [ 0.14205133]
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 [ 0.86696369]
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 [ 4.47496327]
 [-0.94647218]
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 [ 0.38320081]
 [-0.3092422 ]
 [ 4.29328333]
 [-1.91136548]]
[[-0.01910112 -0.30746636  0.26530082 ..., -0.23289238 -0.32864446
   0.27136607]
 [ 0.05779672  0.14209854 -0.00318496 ..., -0.22333514  1.60650093
   0.11028183]
 [-0.06104036  0.25884875  0.46822329 ...,  0.23533844 -0.3018256
   0.96225969]
 ..., 
 [-0.18377959 -0.23560305 -0.37918385 ...,  0.09166135 -0.59926361
  -0.3212372 ]
 [-0.27540736 -0.18360556 -0.18285877 ..., -0.11810011 -0.14889447
  -0.34608418]
 [ 0.03875284  0.08283201 -0.04338233 ...,  0.05281224  2.89955978
  -0.07443502]]
Progress: 79.4% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16112182]
 [-0.95390339]
 [-1.18937826]
 [-0.76699679]
 [-0.05832577]
 [ 2.62693864]
 [-0.04957371]
 [-1.09454644]
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 [ 1.01425551]
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 [ 0.1432851 ]
 [-0.10222579]
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 [ 0.13843649]
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 [ 4.47521068]
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 [-1.64533539]
 [ 0.38365104]
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 [ 4.29566245]
 [-1.91036325]]
[[-0.01912007 -0.30751209  0.2650191  ..., -0.23292866 -0.32809934
   0.27112094]
 [ 0.05789792  0.14271307 -0.00290041 ..., -0.22315177  1.60632978
   0.11115821]
 [-0.06093473  0.25935724  0.46846316 ...,  0.2355254  -0.30216336
   0.96144057]
 ..., 
 [-0.18379558 -0.23568155 -0.37951568 ...,  0.09163539 -0.59770569
  -0.32130738]
 [-0.27548124 -0.18403112 -0.18338892 ..., -0.11823    -0.14820694
  -0.34664332]
 [ 0.03879208  0.08304291 -0.04335941 ...,  0.05288879  2.89951248
  -0.07384647]]
Progress: 79.4% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16180329]
 [-0.95544006]
 [-1.19180919]
 [-0.76816162]
 [-0.05983557]
 [ 2.62658632]
 [-0.05055787]
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 [-0.52762253]
 [ 1.01323339]
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 [ 0.14200893]
 [-0.10325299]
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 [ 0.86742416]
 [-0.83748345]
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 [ 0.38281986]
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 [ 4.29411036]
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[[ -1.90580893e-02  -3.07181967e-01   2.65053401e-01 ...,  -2.32824629e-01
   -3.31219414e-01   2.72104067e-01]
 [  5.79294133e-02   1.42882283e-01  -2.69129213e-03 ...,  -2.23094565e-01
    1.60617202e+00   1.11390679e-01]
 [ -6.08302783e-02   2.59907707e-01   4.69104693e-01 ...,   2.35708604e-01
   -3.04643402e-01   9.62910221e-01]
 ..., 
 [ -1.83762624e-01  -2.35505237e-01  -3.79329227e-01 ...,   9.17121601e-02
   -5.97713462e-01  -3.21224630e-01]
 [ -2.75406698e-01  -1.83591273e-01  -1.82719006e-01 ...,  -1.18109004e-01
   -1.49841599e-01  -3.45565969e-01]
 [  3.88576989e-02   8.34491424e-02  -4.29272138e-02 ...,   5.30105963e-02
    2.89943146e+00  -7.35548507e-02]]
Progress: 79.4% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16395935]
 [-0.9566512 ]
 [-1.19041515]
 [-0.77161782]
 [-0.06208178]
 [ 2.62546857]
 [-0.05352355]
 [-1.09921701]
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 [ 1.01373236]
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 [ 0.86590007]
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 [ 4.47556771]
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 [ 0.38138343]
 [-0.31089045]
 [ 4.29034153]
 [-1.91139824]]
[[ -1.89814775e-02  -3.06734855e-01   2.65038650e-01 ...,  -2.32675771e-01
   -3.31158092e-01   2.72046898e-01]
 [  5.81294942e-02   1.43993940e-01  -1.91011654e-03 ...,  -2.22724403e-01
    1.60473216e+00   1.13180992e-01]
 [ -6.09756013e-02   2.59004265e-01   4.68073983e-01 ...,   2.35455368e-01
   -3.03607276e-01   9.61393452e-01]
 ..., 
 [ -1.83711615e-01  -2.35188091e-01  -3.79681383e-01 ...,   9.18095755e-02
   -5.96735399e-01  -3.20822181e-01]
 [ -2.75287488e-01  -1.82917724e-01  -1.82189131e-01 ...,  -1.17894743e-01
   -1.50878200e-01  -3.44925064e-01]
 [  3.87710843e-02   8.29303267e-02  -4.33837163e-02 ...,   5.28461337e-02
    2.89952909e+00  -7.45743513e-02]]
Progress: 79.4% ... Training loss: 0.063 ... Validation loss: 0.135[[-0.16015813]
 [-0.95451366]
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 [-0.10250275]
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 [ 0.13909406]
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 [ 4.47703663]
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 [-1.64486271]
 [ 0.38396139]
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[[ -1.92507320e-02  -3.08212816e-01   2.63889597e-01 ...,  -2.33166697e-01
   -3.25778613e-01   2.70296456e-01]
 [  5.81397507e-02   1.44069540e-01  -1.76553532e-03 ...,  -2.22698310e-01
    1.60445208e+00   1.13361693e-01]
 [ -6.08280670e-02   2.59854478e-01   4.68063671e-01 ...,   2.35738283e-01
   -3.01394177e-01   9.60708738e-01]
 ..., 
 [ -1.83715441e-01  -2.35190915e-01  -3.79768331e-01 ...,   9.18035103e-02
   -5.95912650e-01  -3.21121740e-01]
 [ -2.75401040e-01  -1.83536404e-01  -1.82803854e-01 ...,  -1.18094300e-01
   -1.48361868e-01  -3.45766916e-01]
 [  3.88087065e-02   8.31076253e-02  -4.30587200e-02 ...,   5.29044685e-02
    2.89940172e+00  -7.37122582e-02]]
Progress: 79.5% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16029519]
 [-0.95442872]
 [-1.19218738]
 [-0.76440958]
 [-0.05711472]
 [ 2.62760082]
 [-0.04883312]
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 [ 0.14306041]
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 [ 0.86921769]
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 [ 0.13908286]
 [-0.35404571]
 [ 4.47566618]
 [-0.94349661]
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 [ 0.38376338]
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 [ 4.29491524]
 [-1.91077849]]
[[ -1.91770117e-02  -3.07731704e-01   2.64865717e-01 ...,  -2.33052050e-01
   -3.26674060e-01   2.71294269e-01]
 [  5.80602999e-02   1.43638108e-01  -2.20093472e-03 ...,  -2.22840063e-01
    1.60438200e+00   1.13033944e-01]
 [ -6.05917353e-02   2.61216333e-01   4.69153185e-01 ...,   2.36176148e-01
   -3.03426423e-01   9.62469594e-01]
 ..., 
 [ -1.83663556e-01  -2.34892154e-01  -3.79649461e-01 ...,   9.19016987e-02
   -5.96671284e-01  -3.20442341e-01]
 [ -2.75549445e-01  -1.84390998e-01  -1.83571633e-01 ...,  -1.18358767e-01
   -1.47335379e-01  -3.47000500e-01]
 [  3.88446148e-02   8.33241998e-02  -4.28036778e-02 ...,   5.29708883e-02
    2.89949985e+00  -7.35553505e-02]]
Progress: 79.5% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.15944474]
 [-0.95297233]
 [-1.19083522]
 [-0.76491857]
 [-0.05647338]
 [ 2.62945877]
 [-0.04811166]
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 [ 1.01396492]
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 [ 0.14405053]
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 [ 0.87082993]
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 [ 4.47546621]
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 [ 0.38541099]
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 [ 4.29692155]
 [-1.91011683]]
[[ -1.92227935e-02  -3.08113814e-01   2.64510450e-01 ...,  -2.33165494e-01
   -3.27229595e-01   2.70441566e-01]
 [  5.79751441e-02   1.43138733e-01  -2.79431812e-03 ...,  -2.23001285e-01
    1.60568094e+00   1.12126114e-01]
 [ -6.07940530e-02   2.60091832e-01   4.68077327e-01 ...,   2.35841430e-01
   -3.02043263e-01   9.61521960e-01]
 ..., 
 [ -1.83680772e-01  -2.34996043e-01  -3.79568113e-01 ...,   9.18827478e-02
   -5.96988876e-01  -3.20401364e-01]
 [ -2.75388571e-01  -1.83506807e-01  -1.82571742e-01 ...,  -1.18073554e-01
   -1.49027865e-01  -3.45760417e-01]
 [  3.88275273e-02   8.32300464e-02  -4.28868105e-02 ...,   5.29418067e-02
    2.89961892e+00  -7.38458356e-02]]
Progress: 79.5% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16211581]
 [-0.95480792]
 [-1.19149536]
 [-0.76787555]
 [-0.05986666]
 [ 2.62864455]
 [-0.05060404]
 [-1.09627942]
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 [ 0.14127228]
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 [ 0.86715465]
 [-0.83732633]
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 [ 0.13724776]
 [-0.35517109]
 [ 4.47399087]
 [-0.94630132]
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 [ 0.38357094]
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 [ 4.29327632]
 [-1.91026574]]
[[ -1.90509517e-02  -3.07161297e-01   2.65249897e-01 ...,  -2.32848016e-01
   -3.31532856e-01   2.71653057e-01]
 [  5.79751441e-02   1.43138733e-01  -2.79431812e-03 ...,  -2.23001285e-01
    1.60568094e+00   1.12126114e-01]
 [ -6.09294287e-02   2.59277337e-01   4.67530297e-01 ...,   2.35607041e-01
   -3.01212957e-01   9.60893950e-01]
 ..., 
 [ -1.83593386e-01  -2.34497834e-01  -3.79112721e-01 ...,   9.20495288e-02
   -5.98202599e-01  -3.20144003e-01]
 [ -2.75362554e-01  -1.83360140e-01  -1.82466794e-01 ...,  -1.18025044e-01
   -1.49002307e-01  -3.45697667e-01]
 [  3.87746783e-02   8.29017103e-02  -4.33418161e-02 ...,   5.28354831e-02
    2.89964084e+00  -7.46979510e-02]]
Progress: 79.5% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15730433]
 [-0.95104503]
 [-1.18881507]
 [-0.76323423]
 [-0.05634897]
 [ 2.63019426]
 [-0.0464272 ]
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 [ 1.01591562]
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 [ 0.144752  ]
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 [ 0.38654297]
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 [ 4.30167585]
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[[-0.01911809 -0.30754116  0.26481915 ..., -0.23296412 -0.33174847
   0.27100285]
 [ 0.05787956  0.14257104 -0.00338723 ..., -0.22318009  1.6061693
   0.11124064]
 [-0.06100182  0.25877837  0.46664544 ...,  0.23547174 -0.3014639
   0.95903901]
 ..., 
 [-0.18366818 -0.23496282 -0.37968084 ...,  0.09191596 -0.59709352
  -0.3207975 ]
 [-0.27532712 -0.18314796 -0.18204478 ..., -0.11795202 -0.14956387
  -0.34512287]
 [ 0.03868467  0.08239011 -0.04382789 ...,  0.05266527  2.89994358
  -0.07557827]]
Progress: 79.5% ... Training loss: 0.063 ... Validation loss: 0.143[[-0.16116227]
 [-0.95393967]
 [-1.19032337]
 [-0.76698277]
 [-0.06035664]
 [ 2.62840371]
 [-0.05001626]
 [-1.09660103]
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 [ 1.01373125]
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 [ 4.29633681]
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[[-0.01897838 -0.30675389  0.26539949 ..., -0.23269656 -0.33294594
   0.27144323]
 [ 0.05783715  0.14232376 -0.00370868 ..., -0.22325226  1.60703818
   0.11074001]
 [-0.06106328  0.25848228  0.46600459 ...,  0.23535156 -0.30356053
   0.9594856 ]
 ..., 
 [-0.18368358 -0.23506704 -0.37972489 ...,  0.09188529 -0.59694296
  -0.32076948]
 [-0.27523747 -0.18261695 -0.1817994  ..., -0.11779205 -0.15170526
  -0.34476926]
 [ 0.03872444  0.08263049 -0.04347477 ...,  0.05273546  2.89988385
  -0.07496139]]
Progress: 79.5% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15961133]
 [-0.95170112]
 [-1.19021479]
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 [ 2.62901375]
 [-0.04841385]
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[[-0.01897863 -0.30671944  0.2657875  ..., -0.23270713 -0.33320283
   0.27169335]
 [ 0.05783693  0.14232006 -0.00373879 ..., -0.22324856  1.60718668
   0.11060773]
 [-0.06098522  0.25893216  0.46610585 ...,  0.23550156 -0.30450035
   0.95924965]
 ..., 
 [-0.18368186 -0.23505682 -0.37965547 ...,  0.0918951  -0.59729557
  -0.32076259]
 [-0.27531479 -0.1830376  -0.18204192 ..., -0.11793615 -0.14940941
  -0.34543352]
 [ 0.03867703  0.08234652 -0.04383065 ...,  0.0526446   2.89995125
  -0.07518823]]
Progress: 79.5% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16328949]
 [-0.95489116]
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 [-0.76776181]
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 [ 1.01294967]
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[[-0.01880345 -0.30564375  0.26677294 ..., -0.23236553 -0.33410126
   0.2735958 ]
 [ 0.05790048  0.14270018 -0.00354966 ..., -0.22313143  1.60681956
   0.11090083]
 [-0.06080093  0.25998205  0.46733094 ...,  0.23585019 -0.30622002
   0.96109345]
 ..., 
 [-0.18365487 -0.23491463 -0.37949774 ...,  0.09194846 -0.59746475
  -0.32054291]
 [-0.27536456 -0.18332064 -0.1824159  ..., -0.11801915 -0.14826699
  -0.34642119]
 [ 0.03869623  0.08242928 -0.04379193 ...,  0.05267084  2.89986151
  -0.0746537 ]]
Progress: 79.5% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.15667991]
 [-0.94957387]
 [-1.18812354]
 [-0.76119522]
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 [ 2.63042607]
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[[-0.01890375 -0.30618775  0.26635487 ..., -0.23257831 -0.33159239
   0.27210549]
 [ 0.05791415  0.1427866  -0.00346798 ..., -0.22311441  1.60676198
   0.11094539]
 [-0.06099496  0.25895119  0.46632634 ...,  0.23549643 -0.29937771
   0.95767249]
 ..., 
 [-0.18369039 -0.23509464 -0.37958982 ...,  0.09187999 -0.59671859
  -0.32082827]
 [-0.27545043 -0.1838021  -0.1829869  ..., -0.11816931 -0.14645622
  -0.34713735]
 [ 0.03861197  0.08190648 -0.0443127  ...,  0.05251606  2.89993358
  -0.0753269 ]]
Progress: 79.5% ... Training loss: 0.065 ... Validation loss: 0.145[[-0.16286726]
 [-0.95579979]
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[[-0.01860301 -0.30444841  0.26817926 ..., -0.23202249 -0.3383088
   0.27527057]
 [ 0.05793205  0.14289451 -0.00333851 ..., -0.22308378  1.60663097
   0.11114017]
 [-0.06063194  0.2611425   0.46898467 ...,  0.23618295 -0.30644029
   0.96182712]
 ..., 
 [-0.18359379 -0.23456374 -0.37912521 ...,  0.09206119 -0.59876584
  -0.32013241]
 [-0.27535313 -0.18323304 -0.1824592  ..., -0.11799465 -0.14791619
  -0.34620115]
 [ 0.03860028  0.0818469  -0.04446514 ...,  0.05249162  2.89995526
  -0.07538375]]
Progress: 79.5% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.15695483]
 [-0.95147315]
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 [-0.76367221]
 [-0.05586354]
 [ 2.62753848]
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[[-0.01901764 -0.30677733  0.26579316 ..., -0.23279958 -0.33320397
   0.27262191]
 [ 0.05791084  0.1427831  -0.00347184 ..., -0.2231298   1.60759287
   0.11099028]
 [-0.06060378  0.26120196  0.46898007 ...,  0.23622932 -0.30581736
   0.96111341]
 ..., 
 [-0.18372893 -0.23530504 -0.37990853 ...,  0.09180387 -0.59751509
  -0.32081431]
 [-0.27534109 -0.18317262 -0.18225065 ..., -0.11796441 -0.14772341
  -0.34587046]
 [ 0.03844001  0.08091765 -0.04528932 ...,  0.0521868   2.90019229
  -0.07686784]]
Progress: 79.5% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.16331867]
 [-0.95730697]
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 [-0.06181506]
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[[-0.01877216 -0.30538147  0.26760231 ..., -0.23234374 -0.33609589
   0.27450881]
 [ 0.05786683  0.14252438 -0.00377363 ..., -0.2232161   1.6078362
   0.11048554]
 [-0.06053876  0.26157577  0.46987929 ...,  0.23637134 -0.30798148
   0.96317323]
 ..., 
 [-0.18371263 -0.23523716 -0.37979702 ...,  0.09183389 -0.59842939
  -0.32072436]
 [-0.27522182 -0.18247925 -0.18146789 ..., -0.11773042 -0.14854059
  -0.34485616]
 [ 0.03854636  0.08156038 -0.04468323 ...,  0.05238178  2.90007466
  -0.07619612]]
Progress: 79.5% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.15544331]
 [-0.94993952]
 [-1.18784272]
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 [-0.05452489]
 [ 2.62779708]
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[[-0.01902383 -0.30678374  0.26617296 ..., -0.23281111 -0.33266608
   0.27264203]
 [ 0.05784745  0.14241541 -0.00391191 ..., -0.22325308  1.60793492
   0.1102893 ]
 [-0.0606205   0.26115137  0.46866018 ...,  0.23624544 -0.30679066
   0.96063398]
 ..., 
 [-0.18372593 -0.23530535 -0.37961416 ...,  0.09181135 -0.59788378
  -0.32100865]
 [-0.27528077 -0.18280533 -0.18191767 ..., -0.11783188 -0.14810474
  -0.3454129 ]
 [ 0.03852119  0.08141212 -0.04493189 ...,  0.05232882  2.90009856
  -0.07603568]]
Progress: 79.5% ... Training loss: 0.064 ... Validation loss: 0.147[[-0.16296502]
 [-0.95579632]
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 [-0.76796316]
 [-0.0608086 ]
 [ 2.6263173 ]
 [-0.05287691]
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[[-0.01877926 -0.30544865  0.26744931 ..., -0.23237515 -0.33621113
   0.27421079]
 [ 0.05790578  0.14275208 -0.00375248 ..., -0.22315578  1.60773073
   0.11052667]
 [-0.06071899  0.26065299  0.46851589 ...,  0.23609899 -0.30752434
   0.96104444]
 ..., 
 [-0.18363    -0.2347691  -0.3790253  ...,  0.09199412 -0.59967574
  -0.32019808]
 [-0.27520319 -0.18234259 -0.18161199 ..., -0.11769736 -0.14890738
  -0.3450611 ]
 [ 0.03853899  0.08150308 -0.04475388 ...,  0.05237032  2.90016252
  -0.07596578]]
Progress: 79.5% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.15765827]
 [-0.95132899]
 [-1.18755728]
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 [ 2.62806962]
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[[-0.01906945 -0.30710972  0.26558368 ..., -0.23290875 -0.33243398
   0.27214626]
 [ 0.05791895  0.14282902 -0.00363313 ..., -0.22313454  1.60759501
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 [-0.18384863 -0.23601631 -0.38060678 ...,  0.09160522 -0.59709198
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  -0.34522583]
 [ 0.03855675  0.0816221  -0.04450302 ...,  0.05240176  2.90001698
  -0.07570908]]
Progress: 79.5% ... Training loss: 0.062 ... Validation loss: 0.144[[-0.15812405]
 [-0.95077201]
 [-1.18805234]
 [-0.76375763]
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 [ 2.62942491]
 [-0.04842481]
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[[-0.01913527 -0.30755744  0.26468338 ..., -0.23303295 -0.33146239
   0.27142636]
 [ 0.05787016  0.14253308 -0.00394118 ..., -0.22322118  1.60837759
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 [-0.18377554 -0.23561133 -0.38031411 ...,  0.0917428  -0.59862035
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  -0.34558857]
 [ 0.03846392  0.08104858 -0.04510932 ...,  0.052219    2.90029695
  -0.07642299]]
Progress: 79.6% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16454471]
 [-0.95580797]
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 [-0.06257178]
 [ 2.62601098]
 [-0.05361372]
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[[-0.01885015 -0.3059786   0.26630951 ..., -0.23251248 -0.33458068
   0.27380651]
 [ 0.05790284  0.1427301  -0.0038214  ..., -0.22315559  1.60815113
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 [-0.18365235 -0.23493459 -0.37957412 ...,  0.09197316 -0.60067836
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  -0.3458114 ]
 [ 0.0385936   0.0818325  -0.04414877 ...,  0.05245423  2.90023742
  -0.0757303 ]]
Progress: 79.6% ... Training loss: 0.064 ... Validation loss: 0.137[[-0.15997293]
 [-0.95186012]
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 [ 2.62805973]
 [-0.04890012]
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[[-0.01913415 -0.30760894  0.26502073 ..., -0.23303205 -0.33160125
   0.27177364]
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 [-0.18370753 -0.23526522 -0.37975186 ...,  0.09187369 -0.60002704
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  -0.34689524]
 [ 0.03862917  0.08198998 -0.04388594 ...,  0.05251519  2.90023457
  -0.07548625]]
Progress: 79.6% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16422487]
 [-0.95500008]
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 [ 2.62677448]
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[[-0.0191357  -0.30767381  0.26530905 ..., -0.23304221 -0.3295374
   0.27186203]
 [ 0.05786653  0.14254437 -0.00384526 ..., -0.22322047  1.60832893
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 [-0.1838617  -0.23616683 -0.38073161 ...,  0.09159264 -0.59805091
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  -0.34675678]
 [ 0.03874478  0.08263203 -0.04316615 ...,  0.05272675  2.90008488
  -0.07482196]]
Progress: 79.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16186223]
 [-0.95232095]
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[[-0.0191678  -0.30786974  0.26541184 ..., -0.23311153 -0.33056467
   0.27189354]
 [ 0.05774949  0.14187735 -0.00458377 ..., -0.22343311  1.60855745
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 [-0.18384455 -0.2360848  -0.38090175 ...,  0.09162491 -0.59898137
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  -0.34712002]
 [ 0.0386659   0.08216697 -0.04364614 ...,  0.05257597  2.90028945
  -0.07552131]]
Progress: 79.6% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16074094]
 [-0.9514404 ]
 [-1.19032869]
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[[-0.01918714 -0.30808973  0.26541938 ..., -0.23314639 -0.3310007
   0.27104583]
 [ 0.05784577  0.14243793 -0.00399802 ..., -0.22325633  1.60823921
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 ..., 
 [-0.18386902 -0.23623296 -0.38117779 ...,  0.09158013 -0.59918281
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  -0.34683396]
 [ 0.03862536  0.08190476 -0.0436616  ...,  0.05250381  2.90033461
  -0.07600898]]
Progress: 79.6% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.15670046]
 [-0.94804448]
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 [-0.05550249]
 [ 2.63033601]
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[[-0.01920308 -0.30820152  0.26524136 ..., -0.23317579 -0.33101747
   0.27072425]
 [ 0.05785923  0.14252054 -0.00390011 ..., -0.22322951  1.6082276
   0.11031206]
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 ..., 
 [-0.18391979 -0.23651593 -0.38146806 ...,  0.09149246 -0.59836101
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 [-0.27545582 -0.18381303 -0.18296086 ..., -0.11818291 -0.14619619
  -0.34711997]
 [ 0.03869133  0.08228322 -0.04317377 ...,  0.0526234   2.90009396
  -0.07504209]]
Progress: 79.6% ... Training loss: 0.066 ... Validation loss: 0.149[[-0.16609923]
 [-0.95515012]
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[[-0.01885622 -0.30622575  0.26665509 ..., -0.23252935 -0.33513791
   0.27364045]
 [ 0.0578956   0.14273561 -0.00369931 ..., -0.22316272  1.60791698
   0.11062773]
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 ..., 
 [-0.18382833 -0.23598566 -0.38104795 ...,  0.09166724 -0.60018243
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  -0.34615351]
 [ 0.03873539  0.08253608 -0.04301342 ...,  0.0527034   2.90016445
  -0.07496769]]
Progress: 79.6% ... Training loss: 0.064 ... Validation loss: 0.136[[-0.16110687]
 [-0.9509044 ]
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[[-0.01900188 -0.30698423  0.26628704 ..., -0.23279127 -0.33415384
   0.27290125]
 [ 0.05787267  0.14260481 -0.00375914 ..., -0.2232027   1.60794845
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 ..., 
 [-0.18393263 -0.23658152 -0.38171583 ...,  0.09147865 -0.59888469
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  -0.34686653]
 [ 0.03859793  0.08173905 -0.04347991 ...,  0.05245157  2.90032963
  -0.07583089]]
Progress: 79.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15660819]
 [-0.94709031]
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[[-0.01912201 -0.30771468  0.2657751  ..., -0.23303021 -0.33398313
   0.27240194]
 [ 0.0577837   0.14208644 -0.00440799 ..., -0.2233598   1.60811345
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   0.95966767]
 ..., 
 [-0.18393798 -0.23660203 -0.38181644 ...,  0.09146683 -0.59856229
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  -0.34572817]
 [ 0.03852442  0.08129427 -0.04392031 ...,  0.05230694  2.90057651
  -0.07657444]]
Progress: 79.6% ... Training loss: 0.066 ... Validation loss: 0.145[[-0.16126432]
 [-0.95048043]
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[[-0.0188231  -0.30599457  0.26758667 ..., -0.23248509 -0.34116638
   0.27515402]
 [ 0.05766972  0.14140274 -0.00516642 ..., -0.22356625  1.60839637
   0.10883616]
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 ..., 
 [-0.18387508 -0.23623398 -0.38128977 ...,  0.09159336 -0.60045767
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  -0.34566815]
 [ 0.0385607   0.08152791 -0.04377    ...,  0.0523794   2.90043173
  -0.07584332]]
Progress: 79.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16096299]
 [-0.94945043]
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[[-0.01875013 -0.30559599  0.26823968 ..., -0.23234862 -0.3420676
   0.27609661]
 [ 0.05771791  0.14168034 -0.00491796 ..., -0.22347373  1.60799071
   0.10912531]
 [-0.06081506  0.2600783   0.46795351 ...,  0.23598979 -0.3121994
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 ..., 
 [-0.18392667 -0.23654031 -0.38165237 ...,  0.09149335 -0.59953938
  -0.32235008]
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  -0.34641203]
 [ 0.03850911  0.08123466 -0.04414819 ...,  0.05228972  2.90058764
  -0.07670474]]
Progress: 79.6% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16417689]
 [-0.95082552]
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[[-0.01870055 -0.30530392  0.26851594 ..., -0.23224437 -0.34170329
   0.2761182 ]
 [ 0.05771161  0.1416399  -0.00494831 ..., -0.22348713  1.60810416
   0.10905435]
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   0.96238898]
 ..., 
 [-0.18394442 -0.23665015 -0.38170885 ...,  0.09146191 -0.59925573
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 [-0.27538553 -0.18344678 -0.18257772 ..., -0.11804875 -0.14695453
  -0.34638083]
 [ 0.03851812  0.08128199 -0.04402412 ...,  0.05229901  2.90051255
  -0.07696694]]
Progress: 79.6% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15858972]
 [-0.94613239]
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 [ 2.62987408]
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[[-0.019152   -0.30785716  0.26588527 ..., -0.23307311 -0.33337457
   0.27277975]
 [ 0.0577076   0.14160952 -0.00499755 ..., -0.22349302  1.60786299
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  -0.34835615]
 [ 0.03842164  0.08072756 -0.0445466  ...,  0.05210641  2.90059915
  -0.07722094]]
Progress: 79.6% ... Training loss: 0.065 ... Validation loss: 0.144[[-0.16863829]
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[[-0.01887008 -0.30625248  0.26749355 ..., -0.23254934 -0.33627791
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 [ 0.03858648  0.08169584 -0.04373652 ...,  0.05240983  2.90043832
  -0.0756995 ]]
Progress: 79.6% ... Training loss: 0.065 ... Validation loss: 0.138[[-0.16467229]
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[[-0.01906952 -0.30729473  0.26628145 ..., -0.23288596 -0.33067577
   0.27369435]
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  -0.34897139]
 [ 0.0385295   0.08137487 -0.04404067 ...,  0.05230883  2.90053782
  -0.07629679]]
Progress: 79.7% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15943232]
 [-0.94720024]
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[[-0.0192169  -0.30812321  0.26511018 ..., -0.23315126 -0.32865836
   0.27196681]
 [ 0.05773338  0.14175738 -0.0048947  ..., -0.22344878  1.60765255
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  -0.34976165]
 [ 0.03847193  0.08103859 -0.04448286 ...,  0.05220299  2.90080669
  -0.07676499]]
Progress: 79.7% ... Training loss: 0.067 ... Validation loss: 0.146[[-0.16433854]
 [-0.95218412]
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 [ 2.62583009]
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[[-0.01911006 -0.3074943   0.26579009 ..., -0.23293697 -0.33220948
   0.27278665]
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  -0.34874154]
 [ 0.03848316  0.08107042 -0.04444697 ...,  0.05222592  2.90082476
  -0.0768777 ]]
Progress: 79.7% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16828821]
 [-0.95517023]
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  -0.34785392]
 [ 0.03850805  0.08118642 -0.0444346  ...,  0.05225965  2.90076841
  -0.07713047]]
Progress: 79.7% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.1627585 ]
 [-0.95072415]
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[[-0.01922539 -0.30823204  0.26473604 ..., -0.23313894 -0.33098109
   0.27119362]
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  -0.3483533 ]
 [ 0.03850092  0.08112339 -0.04451801 ...,  0.05224542  2.90068306
  -0.07725261]]
Progress: 79.7% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16775557]
 [-0.95420838]
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   0.27449739]
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 [ 0.03855267  0.08142683 -0.04429521 ...,  0.05234022  2.90063448
  -0.07684253]]
Progress: 79.7% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16316804]
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[[-0.01906675 -0.30731515  0.26536988 ..., -0.2328688  -0.33207293
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 [ 0.03853166  0.08130807 -0.04437782 ...,  0.05230654  2.90063564
  -0.07743868]]
Progress: 79.7% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16381057]
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[[-0.01890736 -0.30637508  0.26635519 ..., -0.23257133 -0.33340774
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 [-0.18414747 -0.23785665 -0.38259917 ...,  0.09110431 -0.59471395
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 [ 0.03859128  0.08167338 -0.04397061 ...,  0.05241307  2.90063653
  -0.07675309]]
Progress: 79.7% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16787375]
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[[-0.01863685 -0.30486439  0.26766575 ..., -0.23209584 -0.33653413
   0.27706744]
 [ 0.05766694  0.14128947 -0.00555625 ..., -0.22355235  1.60848222
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 [-0.18414476 -0.23784654 -0.382486   ...,  0.09110709 -0.59479371
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 [ 0.0386271   0.08185086 -0.04373018 ...,  0.05247023  2.90056892
  -0.07647525]]
Progress: 79.7% ... Training loss: 0.064 ... Validation loss: 0.139[[-0.16024432]
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[[-0.0188807  -0.30622716  0.26618556 ..., -0.23252782 -0.33355124
   0.27428047]
 [ 0.057643    0.14114847 -0.0057381  ..., -0.22359479  1.60858367
   0.10841264]
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 ..., 
 [-0.18422837 -0.23830669 -0.38290729 ...,  0.09095761 -0.59420688
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 [ 0.0385056   0.08114889 -0.0444024  ...,  0.05225022  2.90079041
  -0.07808926]]
Progress: 79.7% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.16445682]
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[[-0.01876397 -0.30561849  0.26662479 ..., -0.23229375 -0.33569615
   0.27511805]
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 ..., 
 [-0.18419055 -0.23807639 -0.38270305 ...,  0.09103589 -0.595218
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  -0.34932589]
 [ 0.03861283  0.08172811 -0.04380464 ...,  0.05245044  2.90066578
  -0.07755702]]
Progress: 79.7% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16482533]
 [-0.94893571]
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[[-0.01874916 -0.3055543   0.26635626 ..., -0.2322786  -0.33665346
   0.27500546]
 [ 0.05757065  0.14075136 -0.00631888 ..., -0.22371764  1.61000052
   0.10746106]
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 ..., 
 [-0.18407584 -0.23744252 -0.38213841 ...,  0.09124216 -0.59620979
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  -0.34913449]
 [ 0.03858715  0.08155071 -0.0441151  ...,  0.05239675  2.90086581
  -0.0781059 ]]
Progress: 79.7% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16741236]
 [-0.95171095]
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[[-0.01859412 -0.30461313  0.26770979 ..., -0.23200826 -0.33834559
   0.2767385 ]
 [ 0.05755717  0.14070046 -0.00622241 ..., -0.22374049  1.61041666
   0.10754627]
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 ..., 
 [-0.18410754 -0.23763402 -0.38221733 ...,  0.09118613 -0.59578323
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 [ 0.0387274   0.08231366 -0.04337179 ...,  0.05264694  2.9005765
  -0.07688839]]
Progress: 79.7% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.15853522]
 [-0.94391125]
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[[-0.01897735 -0.30670884  0.26519988 ..., -0.23269031 -0.33285018
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 [ 0.03855259  0.08133281 -0.04455624 ...,  0.05232665  2.90089125
  -0.07815709]]
Progress: 79.7% ... Training loss: 0.068 ... Validation loss: 0.145[[-0.16718213]
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 [ 2.62489911]
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[[-0.0185616  -0.30433604  0.26779117 ..., -0.23191856 -0.33665879
   0.27719596]
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  -0.34885447]
 [ 0.0388475   0.08300034 -0.04258907 ...,  0.05288576  2.90024871
  -0.07601424]]
Progress: 79.7% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.16146209]
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  -0.34928517]
 [ 0.03877135  0.08255272 -0.04321764 ...,  0.052747    2.90024086
  -0.07620272]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16143172]
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   0.27621597]
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 [ 0.038739    0.08236692 -0.04348026 ...,  0.0526802   2.90061473
  -0.07696432]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16542271]
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 [ 0.03887106  0.08313217 -0.04290126 ...,  0.05291648  2.90066835
  -0.07656564]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16440148]
 [-0.95295586]
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[[-0.01864721 -0.30465095  0.26714876 ..., -0.2320763  -0.33536761
   0.27632756]
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  -0.34760562]
 [ 0.03896119  0.08363793 -0.04233731 ...,  0.0530884   2.90058291
  -0.07583367]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.1655152 ]
 [-0.95336933]
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[[-0.01872119 -0.30495411  0.2672448  ..., -0.23219463 -0.33338568
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 [ 0.03907603  0.08430638 -0.04147712 ...,  0.0533094   2.90051544
  -0.07496676]]
Progress: 79.8% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16415759]
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[[-0.01876828 -0.30513769  0.26687384 ..., -0.23227161 -0.33139289
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 [ 0.03902643  0.08405413 -0.04183658 ...,  0.05322141  2.90056916
  -0.07522991]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15801488]
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[[-0.01916478 -0.30742571  0.26444214 ..., -0.23301686 -0.32605504
   0.27230836]
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 [-0.18448792 -0.23981289 -0.38445053 ...,  0.09050798 -0.59132571
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 [ 0.03902425  0.08403542 -0.04191815 ...,  0.05321132  2.90049102
  -0.07528223]]
Progress: 79.8% ... Training loss: 0.066 ... Validation loss: 0.149[[-0.16373238]
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[[-0.01896401 -0.30630428  0.26578095 ..., -0.23265136 -0.33034144
   0.27444538]
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 [-0.18451327 -0.23998508 -0.38464945 ...,  0.09046237 -0.5911796
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 [ 0.03905147  0.08421676 -0.04193803 ...,  0.05325911  2.90042626
  -0.07520712]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16308592]
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[[-0.01890609 -0.30595263  0.26610829 ..., -0.23255458 -0.32982007
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 [-0.18453946 -0.24013415 -0.3848703  ...,  0.09040696 -0.59065261
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  -0.34761199]
 [ 0.03911492  0.0845672  -0.04149989 ...,  0.05336933  2.90045418
  -0.07480287]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16406068]
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[[-0.01891689 -0.30596928  0.26589953 ..., -0.23255943 -0.33011684
   0.27484309]
 [ 0.05774364  0.14171217 -0.00504558 ..., -0.22341818  1.60966586
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 [-0.1845866  -0.24038339 -0.38534498 ...,  0.09031378 -0.5900651
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 [ 0.03898269  0.08380888 -0.04195836 ...,  0.0531241   2.90060944
  -0.07574723]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16253492]
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[[-0.01883391 -0.30551045  0.26602754 ..., -0.23240171 -0.32964514
   0.27582918]
 [ 0.05770806  0.14150912 -0.00516496 ..., -0.2234829   1.6096086
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 ..., 
 [-0.18458219 -0.24037424 -0.38542508 ...,  0.09033349 -0.59045743
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  -0.34791257]
 [ 0.03909877  0.08448092 -0.04135137 ...,  0.05333575  2.9005839
  -0.07452111]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16377561]
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[[-0.01886966 -0.3057276   0.26522676 ..., -0.23249491 -0.32820443
   0.2751543 ]
 [ 0.05758824  0.14080264 -0.00604534 ..., -0.22370695  1.61124836
   0.10748061]
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 ..., 
 [-0.18450194 -0.23986957 -0.38514721 ...,  0.09048006 -0.59105398
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  -0.34736709]
 [ 0.03910762  0.08453235 -0.0413783  ...,  0.05335269  2.90053423
  -0.07462287]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16432412]
 [-0.95315639]
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[[-0.01878491 -0.30531472  0.26553974 ..., -0.23233789 -0.32955573
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 [ 0.03911284  0.08457989 -0.04137544 ...,  0.05337149  2.90067888
  -0.07476875]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1617306 ]
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[[-0.01886026 -0.30574855  0.2649762  ..., -0.2324815  -0.32790408
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 [ 0.03910446  0.08453503 -0.04159354 ...,  0.05335469  2.90065391
  -0.07501099]]
Progress: 79.8% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16024438]
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[[-0.01893036 -0.30607928  0.26442639 ..., -0.23259185 -0.32608724
   0.27489213]
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 [ 0.03914648  0.08480426 -0.0413257  ...,  0.05342861  2.90080837
  -0.07469952]]
Progress: 79.8% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16255934]
 [-0.95221201]
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   0.27556302]
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  -0.34749295]
 [ 0.03905812  0.08426456 -0.04185432 ...,  0.05325425  2.90104061
  -0.07557918]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.15830769]
 [-0.94838651]
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[[-0.01889481 -0.30588528  0.26474926 ..., -0.23253797 -0.32808464
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 [-0.18435883 -0.2391005  -0.38500879 ...,  0.09073668 -0.591806   -0.3268574 ]
 [-0.27521777 -0.1825657  -0.1813112  ..., -0.11778199 -0.14204307
  -0.34679512]
 [ 0.03893412  0.08356449 -0.04245069 ...,  0.05302192  2.90111522
  -0.07660836]]
Progress: 79.9% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16399228]
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[[-0.01880378 -0.30544098  0.26523702 ..., -0.23237558 -0.3317759
   0.27608788]
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  -0.34649991]
 [ 0.03893391  0.08352668 -0.04229778 ...,  0.05300786  2.90124489
  -0.07656115]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.15918993]
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[[-0.01908641 -0.30696961  0.26340385 ..., -0.23287688 -0.32832078
   0.27419276]
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  -0.34699175]
 [ 0.03893452  0.08355289 -0.0423458  ...,  0.0530144   2.90119764
  -0.07633087]]
Progress: 79.9% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16122845]
 [-0.94984862]
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  -0.34713787]
 [ 0.03892123  0.08347527 -0.04244072 ...,  0.05299066  2.9013826
  -0.07697235]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16105571]
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[[-0.01928895 -0.30833722  0.26228956 ..., -0.23327386 -0.3289841
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  -0.34695423]
 [ 0.03871035  0.08226099 -0.04360326 ...,  0.05259763  2.90209978
  -0.0792135 ]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16182039]
 [-0.95044839]
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[[-0.01915266 -0.30753821  0.26324014 ..., -0.23301742 -0.33005065
   0.27352488]
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 [-0.18429233 -0.23873948 -0.38478439 ...,  0.09085    -0.59235935
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 [ 0.03875237  0.08251276 -0.04341203 ...,  0.05267906  2.90191344
  -0.07857299]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16002334]
 [-0.94955188]
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[[-0.01924601 -0.30802451  0.26308504 ..., -0.23318926 -0.3283357
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 ..., 
 [-0.18431927 -0.23889591 -0.38475425 ...,  0.09080428 -0.59234188
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 [ 0.0387055   0.08223319 -0.0436572  ...,  0.05258513  2.90201064
  -0.07886169]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16196324]
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[[-0.01919874 -0.30778667  0.26328708 ..., -0.23309526 -0.32933763
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 ..., 
 [-0.18430044 -0.23880212 -0.38469662 ...,  0.0908288  -0.59257732
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  -0.34588519]
 [ 0.03861449  0.08170947 -0.04411339 ...,  0.05242263  2.90231016
  -0.07989931]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16251539]
 [-0.95058805]
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[[-0.01922361 -0.30792247  0.26328436 ..., -0.23312105 -0.32900724
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 ..., 
 [-0.18435105 -0.23906876 -0.38496355 ...,  0.09074299 -0.59192338
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  -0.34607747]
 [ 0.03854088  0.08131273 -0.04460541 ...,  0.05229613  2.90252345
  -0.08091122]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15864868]
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[[-0.01954741 -0.30972898  0.26166407 ..., -0.23370011 -0.32522406
   0.27106033]
 [ 0.05779491  0.14196845 -0.00489569 ..., -0.22332752  1.61068283
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 ..., 
 [-0.1843649  -0.23913578 -0.38502565 ...,  0.09071665 -0.59179164
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  -0.34690182]
 [ 0.03850225  0.08109892 -0.04493246 ...,  0.05222081  2.90290748
  -0.08168948]]
Progress: 79.9% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16102523]
 [-0.94919477]
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[[-0.0194312  -0.3091359   0.26232264 ..., -0.23347596 -0.32845624
   0.2724101 ]
 [ 0.05780562  0.14203125 -0.00481815 ..., -0.22330752  1.61062423
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 ..., 
 [-0.18427919 -0.23864016 -0.3845731  ...,  0.09087288 -0.59318564
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 [ 0.03846729  0.08089831 -0.04519864 ...,  0.05215204  2.90289663
  -0.08155429]]
Progress: 79.9% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15963712]
 [-0.94791025]
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[[-0.01943636 -0.30918531  0.26231269 ..., -0.23349773 -0.32751317
   0.27250105]
 [ 0.05779742  0.14197808 -0.0048939  ..., -0.22332291  1.61063321
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 [-0.1841996  -0.2382159  -0.38399992 ...,  0.09101889 -0.59405447
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 [ 0.03842512  0.08065898 -0.04536776 ...,  0.05206844  2.90289144
  -0.08179216]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16034851]
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 [ 2.63820973]
 [-0.04814493]
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 [ 0.03856006  0.081404   -0.04426074 ...,  0.05233232  2.90291869
  -0.0804715 ]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16432394]
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   0.27703466]
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  -0.34780449]
 [ 0.03870172  0.08222575 -0.04353772 ...,  0.05260555  2.9029119
  -0.07926801]]
Progress: 79.9% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15748502]
 [-0.94587357]
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 [-0.05551632]
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[[-0.019214   -0.30787319  0.26388754 ..., -0.23305968 -0.32855369
   0.27468512]
 [ 0.05772802  0.14155063 -0.00491991 ..., -0.22344293  1.610788
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 [-0.18426265 -0.23863855 -0.38456383 ...,  0.09088882 -0.59311364
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  -0.34883674]
 [ 0.03861401  0.08171823 -0.04395441 ...,  0.05244333  2.9030251
  -0.07982523]]
Progress: 80.0% ... Training loss: 0.065 ... Validation loss: 0.146[[-0.16234748]
 [-0.94999643]
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 [-0.04974677]
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[[-0.01899657 -0.30669243  0.26455507 ..., -0.23266274 -0.33403373
   0.27594984]
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 [-0.18418123 -0.23820333 -0.38430306 ...,  0.09104133 -0.59427028
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  -0.3489862 ]
 [ 0.03855708  0.08134298 -0.04434437 ...,  0.05233463  2.90317165
  -0.08011018]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.16139595]
 [-0.94925933]
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[[-0.01912079 -0.30731119  0.2639929  ..., -0.23291988 -0.33233959
   0.2758131 ]
 [ 0.05772589  0.14156056 -0.00497654 ..., -0.22343485  1.61132902
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 [-0.18419644 -0.23828277 -0.3843591  ...,  0.09101903 -0.59426535
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  -0.34836225]
 [ 0.03862042  0.08174801 -0.04392049 ...,  0.05244662  2.90312239
  -0.0796458 ]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15902778]
 [-0.94682068]
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[[-0.01915462 -0.30753614  0.26371298 ..., -0.23298816 -0.33230931
   0.27499311]
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 [-0.18420766 -0.23834769 -0.3845057  ...,  0.09099998 -0.59420895
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  -0.34879738]
 [ 0.03861966  0.08175456 -0.04387587 ...,  0.05244526  2.9032263
  -0.08024688]]
Progress: 80.0% ... Training loss: 0.063 ... Validation loss: 0.140[[-0.16102025]
 [-0.94936378]
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[[-0.01898209 -0.30655007  0.26443663 ..., -0.23264722 -0.33555697
   0.27623369]
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 [-0.18416699 -0.23810232 -0.38422804 ...,  0.09108346 -0.59452968
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  -0.3484728 ]
 [ 0.03868591  0.08209479 -0.04337253 ...,  0.05257189  2.90310813
  -0.07940783]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.15886297]
 [-0.94727922]
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 [-0.05772053]
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[[-0.01898462 -0.30656326  0.26432    ..., -0.23265337 -0.33563712
   0.27629259]
 [ 0.0576804   0.1412943  -0.00529353 ..., -0.22352387  1.61168734
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 [-0.18418187 -0.23820991 -0.38437583 ...,  0.0910569  -0.59407377
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 [ 0.03856817  0.08141965 -0.04408341 ...,  0.05235635  2.90320017
  -0.08043638]]
Progress: 80.0% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16127552]
 [-0.94919308]
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[[-0.01889386 -0.30607989  0.26462812 ..., -0.23249477 -0.33784021
   0.27631807]
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 [-0.18420002 -0.23833126 -0.38465073 ...,  0.09102228 -0.59397167
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 [ 0.0386374   0.08182755 -0.04366433 ...,  0.0524887   2.90303918
  -0.08004824]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.16048166]
 [-0.94901468]
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[[-0.01904222 -0.30698728  0.26406944 ..., -0.23275885 -0.33343744
   0.27487402]
 [ 0.05765107  0.14111727 -0.00555942 ..., -0.2235674   1.61250789
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 ..., 
 [-0.18425202 -0.23862876 -0.38479811 ...,  0.09092539 -0.59335699
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  -0.34901449]
 [ 0.03884481  0.08300949 -0.04248284 ...,  0.05287672  2.90278116
  -0.07857493]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16643569]
 [-0.95340386]
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[[-0.01877395 -0.30551711  0.2659526  ..., -0.23226381 -0.33725469
   0.27717413]
 [ 0.05768648  0.14130601 -0.00536961 ..., -0.22350396  1.61217588
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 ..., 
 [-0.18416745 -0.23815355 -0.38422522 ...,  0.09108541 -0.59512333
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  -0.34827646]
 [ 0.03894041  0.08357448 -0.04177803 ...,  0.05305986  2.9026752
  -0.07726028]]
Progress: 80.0% ... Training loss: 0.066 ... Validation loss: 0.136[[-0.15825482]
 [-0.94656781]
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[[-0.01889876 -0.30616952  0.26535736 ..., -0.23247639 -0.33596236
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 [ 0.05765079  0.14112118 -0.00545159 ..., -0.22356361  1.61235199
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 ..., 
 [-0.18418416 -0.23821608 -0.38425681 ...,  0.0910594  -0.59562154
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  -0.34881998]
 [ 0.0389319   0.08353317 -0.04179247 ...,  0.05304667  2.90276192
  -0.07740894]]
Progress: 80.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.15921868]
 [-0.94704982]
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[[-0.01883677 -0.3058534   0.26568976 ..., -0.23237275 -0.33868549
   0.27671208]
 [ 0.05763319  0.14102713 -0.00556357 ..., -0.2235938   1.61257821
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 ..., 
 [-0.18418779 -0.23825126 -0.38436485 ...,  0.09105712 -0.59600142
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  -0.34888832]
 [ 0.03896995  0.08373767 -0.04152348 ...,  0.05311236  2.90277545
  -0.0771053 ]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16021539]
 [-0.94777003]
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[[-0.01894965 -0.30653718  0.26495871 ..., -0.23258036 -0.33965773
   0.275739  ]
 [ 0.05764887  0.14111675 -0.00553125 ..., -0.22356394  1.61264624
   0.10810992]
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 [-0.18413184 -0.23792657 -0.38432485 ...,  0.09116437 -0.59581968
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 [-0.27519709 -0.18259513 -0.18036533 ..., -0.1177778  -0.14231559
  -0.348823  ]
 [ 0.0388729   0.08314985 -0.04202422 ...,  0.0529233   2.90301193
  -0.07790296]]
Progress: 80.0% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1639473 ]
 [-0.95126835]
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[[-0.01862911 -0.30464369  0.26657559 ..., -0.23199463 -0.33992199
   0.27921798]
 [ 0.05783397  0.14219739 -0.00447146 ..., -0.2232391   1.61132663
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  -0.34968115]
 [ 0.03897179  0.08373028 -0.04142717 ...,  0.05311007  2.90284854
  -0.07714378]]
Progress: 80.0% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.15554828]
 [-0.94404684]
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 [ 2.64242925]
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[[-0.01896845 -0.30655164  0.26445964 ..., -0.23260331 -0.33393315
   0.27631017]
 [ 0.05782253  0.14213441 -0.0044936  ..., -0.22325721  1.61135241
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 [-0.18426283 -0.23866715 -0.38505387 ...,  0.09093326 -0.59335129
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  -0.35040573]
 [ 0.03897077  0.083719   -0.04169077 ...,  0.05310807  2.90300721
  -0.07755306]]
Progress: 80.0% ... Training loss: 0.068 ... Validation loss: 0.147[[-0.16493051]
 [-0.95212065]
 [-1.19175805]
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 [-0.06260666]
 [ 2.63763798]
 [-0.05176459]
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[[-0.01852754 -0.30402071  0.26714273 ..., -0.23179676 -0.33935108
   0.2801768 ]
 [ 0.05793222  0.14276906 -0.00390438 ..., -0.22304501  1.61099234
   0.11115519]
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 [-0.1841953  -0.23829123 -0.38459773 ...,  0.09105853 -0.59476933
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  -0.34976271]
 [ 0.03908006  0.08436708 -0.04095199 ...,  0.05330993  2.90286179
  -0.07681574]]
Progress: 80.0% ... Training loss: 0.064 ... Validation loss: 0.135[[-0.1541992 ]
 [-0.94290856]
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 [ 2.642803  ]
 [-0.04316135]
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[[-0.01901074 -0.30677022  0.2642554  ..., -0.23267911 -0.33417053
   0.27619103]
 [ 0.05792244  0.14271094 -0.003952   ..., -0.22306203  1.61102876
   0.11108986]
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 [-0.18424149 -0.23853462 -0.38486454 ...,  0.09096183 -0.59375803
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  -0.35046777]
 [ 0.03895542  0.08366062 -0.04175991 ...,  0.05307917  2.90336516
  -0.07826344]]
Progress: 80.1% ... Training loss: 0.070 ... Validation loss: 0.150[[-0.16296334]
 [-0.95033209]
 [-1.19261207]
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 [ 2.63948254]
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[[-0.0188689  -0.30593138  0.26516381 ..., -0.23241105 -0.33641212
   0.2785695 ]
 [ 0.05805602  0.14352597 -0.0031727  ..., -0.22281341  1.60975005
   0.11274252]
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 [-0.18418983 -0.23822963 -0.38454223 ...,  0.09106117 -0.59471905
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  -0.3502134 ]
 [ 0.03895473  0.08362296 -0.04169358 ...,  0.05306142  2.90347477
  -0.0783861 ]]
Progress: 80.1% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.15836386]
 [-0.94668176]
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 [ 2.64264221]
 [-0.04593409]
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[[-0.01900815 -0.30668573  0.26435711 ..., -0.23267429 -0.3351407
   0.2779435 ]
 [ 0.05796135  0.14299003 -0.00378269 ..., -0.22299278  1.61052273
   0.1117293 ]
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   0.95831609]
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 [-0.18422387 -0.2384182  -0.38476754 ...,  0.09100579 -0.5944871
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  -0.34934417]
 [ 0.03878773  0.08267918 -0.04275989 ...,  0.05275162  2.90401429
  -0.08016945]]
Progress: 80.1% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.15878852]
 [-0.9473691 ]
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 [-0.05887351]
 [ 2.64316052]
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[[-0.01904327 -0.30694673  0.26402667 ..., -0.2327433  -0.33479152
   0.277657  ]
 [ 0.05795138  0.14293344 -0.00385354 ..., -0.22301124  1.61081424
   0.11157912]
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  -0.34925063]
 [ 0.03882959  0.08292909 -0.04259778 ...,  0.05282432  2.90392145
  -0.07993059]]
Progress: 80.1% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.15991789]
 [-0.9482989 ]
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[[-0.01911418 -0.30737368  0.26354699 ..., -0.23286131 -0.33293362
   0.27655522]
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 [-0.18421294 -0.23838779 -0.38504658 ...,  0.09102368 -0.59492562
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  -0.34959026]
 [ 0.03886878  0.08314345 -0.04224786 ...,  0.05289441  2.90392913
  -0.07943916]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16493951]
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[[-0.01896446 -0.30640553  0.26447656 ..., -0.23258414 -0.33305784
   0.27789829]
 [ 0.05796928  0.14305388 -0.00364585 ..., -0.22297985  1.6108058
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 [-0.1841513  -0.2380143  -0.3847556  ...,  0.0911388  -0.59585813
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  -0.35005628]
 [ 0.03896141  0.08370078 -0.04157635 ...,  0.05307525  2.9036807
  -0.07842328]]
Progress: 80.1% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.15827904]
 [-0.94723554]
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[[-0.01932831 -0.30839147  0.26271224 ..., -0.23325395 -0.32548033
   0.27537531]
 [ 0.05793489  0.14285165 -0.00392692 ..., -0.22304639  1.61162402
   0.11139484]
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 ..., 
 [-0.18422777 -0.23844134 -0.38517486 ...,  0.09099704 -0.59463102
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  -0.35097695]
 [ 0.03892251  0.08346684 -0.0417646  ...,  0.05300811  2.90354667
  -0.07821174]]
Progress: 80.1% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.16126744]
 [-0.94948002]
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[[-0.01912696 -0.30712941  0.26427123 ..., -0.23288421 -0.32622733
   0.27787157]
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 ..., 
 [-0.1842235  -0.23841212 -0.38528551 ...,  0.09100563 -0.59471806
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  -0.35125494]
 [ 0.03905757  0.08427528 -0.04073419 ...,  0.05327157  2.9032667
  -0.07670475]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.1629124 ]
 [-0.95148128]
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 [ 2.64007672]
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[[-0.01916568 -0.30742045  0.26415827 ..., -0.23296622 -0.32537709
   0.27791922]
 [ 0.05791435  0.14273965 -0.00389845 ..., -0.22309119  1.61199397
   0.11134695]
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 [-0.18423574 -0.23848918 -0.38535441 ...,  0.09098315 -0.59438002
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 [-0.27512066 -0.18227032 -0.18045754 ..., -0.11765783 -0.13992874
  -0.35005031]
 [ 0.0390657   0.08430831 -0.0409761  ...,  0.0532787   2.90344482
  -0.07676006]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16070059]
 [-0.94950135]
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[[-0.01920745 -0.30764525  0.26382586 ..., -0.23304955 -0.32608283
   0.27736329]
 [ 0.05787077  0.14248256 -0.00412298 ..., -0.22317398  1.61250031
   0.11101829]
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   0.96161933]
 ..., 
 [-0.18419949 -0.2382822  -0.3852826  ...,  0.09104657 -0.59491642
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  -0.35042782]
 [ 0.03889023  0.08330705 -0.04201558 ...,  0.0529454   2.90371351
  -0.07822928]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16237234]
 [-0.95202151]
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[[-0.01898985 -0.30645954  0.26516375 ..., -0.23266877 -0.32994886
   0.27951882]
 [ 0.0578321   0.14225244 -0.00424757 ..., -0.22324581  1.61295119
   0.11071956]
 [-0.06038012  0.26269311  0.46593092 ...,  0.23711041 -0.31141356
   0.96322348]
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 [-0.18417642 -0.2381889  -0.38500834 ...,  0.09108476 -0.59524212
  -0.32516706]
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  -0.3499843 ]
 [ 0.0388822   0.08326269 -0.04218495 ...,  0.05292974  2.90376702
  -0.07841943]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16459313]
 [-0.9542032 ]
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[[-0.01878934 -0.30527092  0.26614866 ..., -0.23228374 -0.3296659
   0.28079007]
 [ 0.05790739  0.14267251 -0.00382679 ..., -0.22311292  1.61304088
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 [ 0.03895671  0.08366042 -0.04170637 ...,  0.05307151  2.9037355
  -0.07768709]]
Progress: 80.1% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.15997517]
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[[-0.01876639 -0.30510954  0.26581676 ..., -0.23223515 -0.32829895
   0.28099599]
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 [ 0.03897055  0.08372607 -0.0415772  ...,  0.05308721  2.90380415
  -0.07766519]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15653881]
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   0.27882105]
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  -0.34837512]
 [ 0.03899282  0.08385756 -0.0415694  ...,  0.05314255  2.90394203
  -0.07768862]]
Progress: 80.1% ... Training loss: 0.064 ... Validation loss: 0.146[[-0.1603411 ]
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  -0.34829861]
 [ 0.03908144  0.08436513 -0.04089665 ...,  0.05331547  2.9036738
  -0.07643584]]
Progress: 80.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15919982]
 [-0.95142451]
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  -0.34961143]
 [ 0.03908244  0.08436364 -0.04084341 ...,  0.05331641  2.90374555
  -0.07628792]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.142[[-0.15986203]
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[[-0.01890494 -0.30599889  0.26479152 ..., -0.23248615 -0.32722102
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 [ 0.0576774   0.14144595 -0.0054043  ..., -0.22351971  1.61643297
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 [ 0.0390489   0.0841792  -0.04105542 ...,  0.0532517   2.90389624
  -0.0768718 ]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.142[[-0.15823652]
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[[-0.0188573  -0.30572032  0.26507344 ..., -0.23238152 -0.32727982
   0.27964496]
 [ 0.05779689  0.14215706 -0.00460022 ..., -0.22330507  1.6160155
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  -0.34985386]
 [ 0.03892849  0.08346273 -0.04173074 ...,  0.05303402  2.90420957
  -0.07767634]]
Progress: 80.2% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16021233]
 [-0.95065147]
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[[-0.01868008 -0.30474305  0.26598824 ..., -0.23204882 -0.32932887
   0.28048801]
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 [ 0.03893238  0.08348527 -0.04161677 ...,  0.05304957  2.90442017
  -0.07759015]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15571155]
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[[-0.01892214 -0.30612379  0.26443933 ..., -0.23251189 -0.32817781
   0.27841782]
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 ..., 
 [-0.18434297 -0.23933433 -0.38579631 ...,  0.0907651  -0.59457607
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 [ 0.03888633  0.0832385  -0.04223603 ...,  0.05296835  2.90477164
  -0.07865574]]
Progress: 80.2% ... Training loss: 0.065 ... Validation loss: 0.149[[-0.16685424]
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[[-0.01847112 -0.30345438  0.2675231  ..., -0.23164903 -0.33245323
   0.28280319]
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 [-0.18418598 -0.23841525 -0.38487588 ...,  0.09106692 -0.59661221
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  -0.34917018]
 [ 0.03901864  0.08400165 -0.04127622 ...,  0.05321162  2.90465434
  -0.077725  ]]
Progress: 80.2% ... Training loss: 0.070 ... Validation loss: 0.139[[-0.1551301 ]
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[[-0.01910691 -0.30695647  0.26401759 ..., -0.23282033 -0.32416777
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 [-0.18447446 -0.24000719 -0.3864616  ...,  0.09052961 -0.5925021
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  -0.34958237]
 [ 0.03892479  0.08349861 -0.04174095 ...,  0.05304196  2.90475612
  -0.07859362]]
Progress: 80.2% ... Training loss: 0.066 ... Validation loss: 0.150[[-0.16071192]
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[[-0.01890361 -0.30583007  0.26530289 ..., -0.23242593 -0.32844666
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   0.10949759]
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 [-0.18425438 -0.23869766 -0.38507499 ...,  0.09094863 -0.595961
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 [ 0.03883182  0.08290561 -0.04218323 ...,  0.05286538  2.90510511
  -0.07954892]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15726323]
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[[-0.01915522 -0.307281    0.26377321 ..., -0.23289042 -0.32469885
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 [ 0.05766825  0.14143026 -0.00533282 ..., -0.22353441  1.61838816
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 ..., 
 [-0.18433837 -0.23917842 -0.38548762 ...,  0.09079363 -0.59400649
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 [-0.27486116 -0.18078135 -0.1798943  ..., -0.11714391 -0.1440721
  -0.34922268]
 [ 0.03880228  0.08271189 -0.04237841 ...,  0.05280533  2.90521421
  -0.07974664]]
Progress: 80.2% ... Training loss: 0.063 ... Validation loss: 0.144[[-0.15984855]
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[[-0.0189541  -0.30614051  0.26525834 ..., -0.23252838 -0.32778341
   0.27872083]
 [ 0.05765011  0.14132493 -0.00543186 ..., -0.22356784  1.61847481
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 ..., 
 [-0.18435953 -0.23932484 -0.38566798 ...,  0.09075803 -0.59430853
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  -0.34893684]
 [ 0.03878052  0.0825364  -0.04233295 ...,  0.05274124  2.90533706
  -0.07992409]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16067675]
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[[-0.0190426  -0.30667115  0.26475454 ..., -0.23269456 -0.3278051
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 [ 0.05761372  0.14110652 -0.00560861 ..., -0.22363596  1.61896877
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 [-0.18432232 -0.23912593 -0.38543228 ...,  0.09082728 -0.59460036
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  -0.34868936]
 [ 0.03882388  0.08280536 -0.04187008 ...,  0.05282328  2.90535848
  -0.07979062]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15986049]
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  -0.07951906]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16062205]
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  -0.08053406]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15947776]
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  -0.08109574]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.15920908]
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 [ 0.03859607  0.08140549 -0.04337869 ...,  0.05238582  2.90578114
  -0.08067576]]
Progress: 80.2% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16040328]
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  -0.08029442]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.1617131 ]
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  -0.07979812]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16113826]
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 [ 0.03886354  0.08295728 -0.04184561 ...,  0.05289403  2.90545581
  -0.0783379 ]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15930494]
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[[-0.01946106 -0.30899442  0.2625972  ..., -0.23343094 -0.32187736
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  -0.07908402]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16333416]
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[[-0.01935611 -0.30840061  0.26315586 ..., -0.23324225 -0.32292015
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 [ 0.03894497  0.08341649 -0.04162219 ...,  0.05303444  2.90547441
  -0.07786633]]
Progress: 80.3% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16013037]
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 [ 0.03877688  0.08243683 -0.04261713 ...,  0.05273935  2.90599532
  -0.07933409]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16306887]
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 [ 0.03874456  0.08224444 -0.04283593 ...,  0.05267103  2.90610999
  -0.07924754]]
Progress: 80.3% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.15934372]
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[[-0.01960577 -0.3099229   0.26191643 ..., -0.23367329 -0.32264381
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 [-0.18421138 -0.23852172 -0.38491632 ...,  0.09106166 -0.59598301
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 [ 0.03869895  0.08198435 -0.04308391 ...,  0.05259111  2.9061461
  -0.0794617 ]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.143[[-0.16370117]
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[[-0.01933072 -0.30836981  0.26346988 ..., -0.23317001 -0.32549617
   0.27579444]
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 [-0.18429292 -0.23898253 -0.38543513 ...,  0.09090811 -0.59437175
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 [ 0.03873346  0.08217257 -0.0429943  ...,  0.05264798  2.90607066
  -0.07903659]]
Progress: 80.3% ... Training loss: 0.063 ... Validation loss: 0.138[[-0.15431135]
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[[-0.0198846  -0.31157639  0.26013759 ..., -0.23418137 -0.31623941
   0.27052799]
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 [-0.18447985 -0.24005171 -0.38679651 ...,  0.09056182 -0.59046346
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 [ 0.03867709  0.08186266 -0.04333286 ...,  0.05254436  2.90612969
  -0.07964589]]
Progress: 80.3% ... Training loss: 0.071 ... Validation loss: 0.159[[-0.16034641]
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[[-0.01955169 -0.30960975  0.26207012 ..., -0.23354052 -0.32288878
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  -0.07994936]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.1633163 ]
 [-0.95559321]
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 [ 2.64759978]
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[[-0.01944102 -0.30893149  0.2629777  ..., -0.23333349 -0.32726445
   0.27452166]
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 [ 0.03856139  0.08117477 -0.04386786 ...,  0.05231417  2.90632342
  -0.08065176]]
Progress: 80.3% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.15786057]
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 [ 0.03855173  0.08110525 -0.04394605 ...,  0.05229369  2.90637997
  -0.08060516]]
Progress: 80.3% ... Training loss: 0.062 ... Validation loss: 0.148[[-0.16217899]
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   0.27550466]
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 [ 0.03857661  0.08126942 -0.04360484 ...,  0.05233966  2.90635136
  -0.07991107]]
Progress: 80.3% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16316785]
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[[-0.01925654 -0.30781862  0.2639548  ..., -0.23297558 -0.3279371
   0.27735829]
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 [ 0.03855723  0.08116824 -0.0435611  ...,  0.05230723  2.90624132
  -0.07920764]]
Progress: 80.3% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16445532]
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[[-0.01912083 -0.30705288  0.26462651 ..., -0.23272364 -0.32951849
   0.27847196]
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  -0.35195965]
 [ 0.03855042  0.08113969 -0.04363957 ...,  0.05229194  2.90632737
  -0.07942301]]
Progress: 80.4% ... Training loss: 0.063 ... Validation loss: 0.139[[-0.15942051]
 [-0.95053302]
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   0.27637735]
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 [ 0.03848415  0.08075278 -0.04381463 ...,  0.05216954  2.90636986
  -0.0799574 ]]
Progress: 80.4% ... Training loss: 0.062 ... Validation loss: 0.146[[-0.16384084]
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[[-0.01910994 -0.30701235  0.26448782 ..., -0.23273734 -0.32698086
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 [ 0.03870386  0.08202996 -0.04235809 ...,  0.05257979  2.90586757
  -0.07763644]]
Progress: 80.4% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16163679]
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[[-0.01923197 -0.30765229  0.26371972 ..., -0.23295901 -0.3254191
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 [ 0.03867553  0.08188324 -0.04255808 ...,  0.05253175  2.90601904
  -0.07783778]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.144[[-0.16003986]
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[[-0.01930853 -0.30810595  0.26303956 ..., -0.23309317 -0.32451121
   0.27686802]
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 [ 0.03871527  0.08212385 -0.04256572 ...,  0.05260695  2.90599268
  -0.07763938]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.144[[-0.16202713]
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[[-0.01925717 -0.3078068   0.26319152 ..., -0.23301252 -0.32517902
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 [ 0.03892936  0.08338947 -0.04144141 ...,  0.05300907  2.9055897
  -0.07595833]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.1586926 ]
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[[-0.01941877 -0.30876941  0.26240534 ..., -0.23336067 -0.32483014
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 [ 0.05803799  0.14354403 -0.00337549 ..., -0.22288377  1.62196646
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 [-0.18412688 -0.23796517 -0.38414032 ...,  0.0912298  -0.59680734
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 [ 0.0388692   0.08303147 -0.04185382 ...,  0.05288026  2.90597309
  -0.07659153]]
Progress: 80.4% ... Training loss: 0.063 ... Validation loss: 0.146[[-0.16357564]
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[[-0.01914247 -0.30716009  0.26412758 ..., -0.23283686 -0.32822359
   0.27885272]
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   0.11182355]
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 ..., 
 [-0.18404563 -0.23752229 -0.38363022 ...,  0.09137217 -0.59874245
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  -0.35184946]
 [ 0.03895115  0.08350495 -0.04123691 ...,  0.05303211  2.90585737
  -0.07598739]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16281404]
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[[-0.01928056 -0.30798383  0.26317733 ..., -0.23308011 -0.3270265
   0.27794123]
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 [-0.18408096 -0.23770464 -0.38377029 ...,  0.09131137 -0.59871962
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  -0.35104399]
 [ 0.03895113  0.08346875 -0.04121253 ...,  0.05304867  2.9058611
  -0.07601634]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15662653]
 [-0.94796412]
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[[-0.0194157  -0.30880366  0.26211237 ..., -0.23331742 -0.32580415
   0.27731967]
 [ 0.05805157  0.14362221 -0.0032863  ..., -0.22286028  1.62175517
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 [-0.18412715 -0.23796709 -0.38385424 ...,  0.09122648 -0.59828933
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 [ 0.03889577  0.08312051 -0.0417742  ...,  0.05293817  2.90575259
  -0.07672061]]
Progress: 80.4% ... Training loss: 0.064 ... Validation loss: 0.150[[-0.16543686]
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 [-1.92174141]]
[[-0.01900806 -0.3064677   0.26458967 ..., -0.23255633 -0.32962     0.28079604]
 [ 0.05808109  0.14380059 -0.00309521 ..., -0.22280465  1.6215248
   0.11207406]
 [-0.06000268  0.2644159   0.46876146 ...,  0.23795292 -0.30218806
   0.96042166]
 ..., 
 [-0.18408742 -0.23775391 -0.38352744 ...,  0.09130108 -0.59864115
  -0.3240138 ]
 [-0.27492905 -0.18131342 -0.18010425 ..., -0.11723302 -0.13898581
  -0.35189376]
 [ 0.03907094  0.08416444 -0.04058503 ...,  0.05326989  2.90553456
  -0.07515405]]
Progress: 80.4% ... Training loss: 0.064 ... Validation loss: 0.139[[-0.15948113]
 [-0.95103304]
 [-1.19487378]
 [-0.76366494]
 [-0.05631899]
 [ 2.64829774]
 [-0.04867424]
 [-1.09469884]
 [-0.53062088]
 [ 1.02794494]
 [-0.09132978]
 [ 0.14306783]
 [-0.09966902]
 [-1.00334156]
 [-0.30276239]
 [ 0.87021036]
 [-0.83622948]
 [-0.79525101]
 [-0.62365159]
 [ 0.13969604]
 [-0.35110926]
 [ 4.48598255]
 [-0.94405242]
 [-1.64686684]
 [ 0.38452832]
 [-0.30621364]
 [ 4.3141935 ]
 [-1.91920296]]
[[ -1.90841826e-02  -3.06811523e-01   2.64318655e-01 ...,  -2.32674561e-01
   -3.29238618e-01   2.80148079e-01]
 [  5.81329689e-02   1.44094775e-01  -2.78645662e-03 ...,  -2.22711044e-01
    1.62138707e+00   1.12441919e-01]
 [ -6.00521428e-02   2.63952146e-01   4.68380678e-01 ...,   2.37832861e-01
   -3.03859871e-01   9.58376783e-01]
 ..., 
 [ -1.84066216e-01  -2.37609199e-01  -3.83340773e-01 ...,   9.13476932e-02
   -5.99489418e-01  -3.23730143e-01]
 [ -2.75010128e-01  -1.81776094e-01  -1.80337254e-01 ...,  -1.17380874e-01
   -1.37885113e-01  -3.52168663e-01]
 [  3.89648618e-02   8.35494104e-02  -4.11441645e-02 ...,   5.30735706e-02
    2.90559811e+00  -7.60772380e-02]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.144[[-0.16116158]
 [-0.95179557]
 [-1.19452463]
 [-0.76570944]
 [-0.05771343]
 [ 2.64713674]
 [-0.05027761]
 [-1.09575266]
 [-0.53053903]
 [ 1.0283008 ]
 [-0.09303312]
 [ 0.14258839]
 [-0.10118314]
 [-1.00461878]
 [-0.30329923]
 [ 0.86990024]
 [-0.83692034]
 [-0.79516383]
 [-0.62311648]
 [ 0.13908672]
 [-0.35160532]
 [ 4.48488338]
 [-0.94735195]
 [-1.64789745]
 [ 0.38357904]
 [-0.30684595]
 [ 4.31197184]
 [-1.91999209]]
[[ -1.90247122e-02  -3.06522507e-01   2.64227924e-01 ...,  -2.32570040e-01
   -3.29548444e-01   2.80417078e-01]
 [  5.82332526e-02   1.44685883e-01  -2.11957390e-03 ...,  -2.22529035e-01
    1.62109022e+00   1.13188042e-01]
 [ -6.00955141e-02   2.63786945e-01   4.68685809e-01 ...,   2.37793289e-01
   -3.03611855e-01   9.58421190e-01]
 ..., 
 [ -1.84136161e-01  -2.38043963e-01  -3.83776729e-01 ...,   9.12241644e-02
   -5.98654937e-01  -3.24079908e-01]
 [ -2.75079572e-01  -1.82213077e-01  -1.80747291e-01 ...,  -1.17517927e-01
   -1.36802023e-01  -3.52968969e-01]
 [  3.89594535e-02   8.35200930e-02  -4.12483454e-02 ...,   5.30586617e-02
    2.90565358e+00  -7.60485884e-02]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.1585125 ]
 [-0.95026978]
 [-1.19424464]
 [-0.76244657]
 [-0.05603953]
 [ 2.64889524]
 [-0.0476412 ]
 [-1.09249496]
 [-0.52928526]
 [ 1.02870552]
 [-0.09048383]
 [ 0.14493185]
 [-0.09814253]
 [-1.00350627]
 [-0.30142808]
 [ 0.87290396]
 [-0.83465601]
 [-0.7942701 ]
 [-0.62186747]
 [ 0.14114295]
 [-0.34940826]
 [ 4.48567645]
 [-0.94501019]
 [-1.64574817]
 [ 0.38557962]
 [-0.30442772]
 [ 4.3166754 ]
 [-1.91931674]]
[[ -1.91916437e-02  -3.07562839e-01   2.63154561e-01 ...,  -2.32871400e-01
   -3.28363092e-01   2.79541367e-01]
 [  5.82360371e-02   1.44703447e-01  -2.06413442e-03 ...,  -2.22521917e-01
    1.62107269e+00   1.13174413e-01]
 [ -6.00195818e-02   2.64239786e-01   4.68847513e-01 ...,   2.37952541e-01
   -3.04611420e-01   9.58619374e-01]
 ..., 
 [ -1.84251012e-01  -2.38699625e-01  -3.84433236e-01 ...,   9.10130350e-02
   -5.96779602e-01  -3.25027858e-01]
 [ -2.75061830e-01  -1.82103721e-01  -1.80943277e-01 ...,  -1.17466743e-01
   -1.37909682e-01  -3.52933662e-01]
 [  3.89088164e-02   8.32300279e-02  -4.14773108e-02 ...,   5.29612889e-02
    2.90587888e+00  -7.64473555e-02]]
Progress: 80.4% ... Training loss: 0.062 ... Validation loss: 0.146[[-0.16058216]
 [-0.95239575]
 [-1.19521599]
 [-0.76555235]
 [-0.05802896]
 [ 2.64825065]
 [-0.0502015 ]
 [-1.09501788]
 [-0.53163734]
 [ 1.02740234]
 [-0.09288349]
 [ 0.14285867]
 [-0.10085676]
 [-1.00525749]
 [-0.3032105 ]
 [ 0.87098067]
 [-0.83682661]
 [-0.79512023]
 [-0.62344373]
 [ 0.13990068]
 [-0.35089781]
 [ 4.48451972]
 [-0.94706526]
 [-1.64715941]
 [ 0.38423593]
 [-0.30716008]
 [ 4.31400606]
 [-1.92079742]]
[[ -1.92117902e-02  -3.07683973e-01   2.63004986e-01 ...,  -2.32875002e-01
   -3.28930334e-01   2.79858376e-01]
 [  5.82824167e-02   1.44973929e-01  -1.85564971e-03 ...,  -2.22439057e-01
    1.62090772e+00   1.13397277e-01]
 [ -5.99326162e-02   2.64771875e-01   4.69706711e-01 ...,   2.38119836e-01
   -3.07373411e-01   9.60049087e-01]
 ..., 
 [ -1.84028188e-01  -2.37406815e-01  -3.82965824e-01 ...,   9.14252925e-02
   -6.00293927e-01  -3.23122350e-01]
 [ -2.74980479e-01  -1.81600440e-01  -1.80440970e-01 ...,  -1.17295371e-01
   -1.37818714e-01  -3.51856855e-01]
 [  3.89430445e-02   8.34618091e-02  -4.14376538e-02 ...,   5.30423879e-02
    2.90592557e+00  -7.62131929e-02]]
Progress: 80.4% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.15968097]
 [-0.95181432]
 [-1.19296092]
 [-0.76634476]
 [-0.05832941]
 [ 2.64884669]
 [-0.05019097]
 [-1.09657221]
 [-0.53000233]
 [ 1.02957511]
 [-0.09229467]
 [ 0.1434826 ]
 [-0.10021578]
 [-1.00431701]
 [-0.30250497]
 [ 0.87209337]
 [-0.83542618]
 [-0.79258305]
 [-0.62182041]
 [ 0.14056573]
 [-0.34996999]
 [ 4.48472472]
 [-0.9471891 ]
 [-1.64739236]
 [ 0.38526279]
 [-0.30659681]
 [ 4.31519551]
 [-1.92002585]]
[[ -1.92155438e-02  -3.07740443e-01   2.62916705e-01 ...,  -2.32874469e-01
   -3.29360569e-01   2.79410842e-01]
 [  5.82896518e-02   1.45014600e-01  -1.79332448e-03 ...,  -2.22425672e-01
    1.62079121e+00   1.13455903e-01]
 [ -6.01521026e-02   2.63488035e-01   4.68754007e-01 ...,   2.37740746e-01
   -3.04370741e-01   9.58755664e-01]
 ..., 
 [ -1.84082025e-01  -2.37718521e-01  -3.83381148e-01 ...,   9.13221797e-02
   -5.99583455e-01  -3.23733197e-01]
 [ -2.74959586e-01  -1.81503272e-01  -1.80240214e-01 ...,  -1.17261914e-01
   -1.38077753e-01  -3.51789133e-01]
 [  3.89432804e-02   8.34451120e-02  -4.15948976e-02 ...,   5.30337618e-02
    2.90593339e+00  -7.63717534e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.15979686]
 [-0.95098711]
 [-1.19414991]
 [-0.7653508 ]
 [-0.05840788]
 [ 2.65014424]
 [-0.04988957]
 [-1.09725638]
 [-0.53006335]
 [ 1.02880283]
 [-0.09201257]
 [ 0.14292161]
 [-0.09978376]
 [-1.00321663]
 [-0.30283335]
 [ 0.8711113 ]
 [-0.83555289]
 [-0.79426488]
 [-0.62284156]
 [ 0.14088686]
 [-0.35086926]
 [ 4.48550835]
 [-0.94593406]
 [-1.64891914]
 [ 0.38488079]
 [-0.30537176]
 [ 4.31528095]
 [-1.91936541]]
[[ -1.92207015e-02  -3.07890878e-01   2.62949371e-01 ...,  -2.32893858e-01
   -3.29669071e-01   2.78990948e-01]
 [  5.82905436e-02   1.45020096e-01  -1.74366203e-03 ...,  -2.22424038e-01
    1.62078628e+00   1.13416900e-01]
 [ -6.03396973e-02   2.62436552e-01   4.67032498e-01 ...,   2.37405390e-01
   -3.00167334e-01   9.57085905e-01]
 ..., 
 [ -1.84115007e-01  -2.37924318e-01  -3.83555166e-01 ...,   9.12643107e-02
   -5.99087648e-01  -3.24185635e-01]
 [ -2.74880040e-01  -1.81129268e-01  -1.79754522e-01 ...,  -1.17123756e-01
   -1.39754376e-01  -3.51562433e-01]
 [  3.90074957e-02   8.38313334e-02  -4.12334276e-02 ...,   5.31546358e-02
    2.90588502e+00  -7.59038904e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16171378]
 [-0.95262146]
 [-1.19594881]
 [-0.76704173]
 [-0.06081168]
 [ 2.65118239]
 [-0.05153952]
 [-1.10057552]
 [-0.53154899]
 [ 1.02514722]
 [-0.09455845]
 [ 0.14030875]
 [-0.10148097]
 [-1.00324225]
 [-0.30446987]
 [ 0.86818817]
 [-0.83728165]
 [-0.79651341]
 [-0.6249053 ]
 [ 0.13921266]
 [-0.35338135]
 [ 4.48563566]
 [-0.94721463]
 [-1.65236503]
 [ 0.38338401]
 [-0.30674443]
 [ 4.31266297]
 [-1.91860946]]
[[ -1.93596890e-02  -3.08691832e-01   2.62243488e-01 ...,  -2.33152963e-01
   -3.27218386e-01   2.77803340e-01]
 [  5.83001192e-02   1.45068022e-01  -1.69683773e-03 ...,  -2.22407204e-01
    1.62074745e+00   1.13475858e-01]
 [ -6.06006957e-02   2.60856756e-01   4.65585476e-01 ...,   2.36922568e-01
   -2.99058262e-01   9.54744207e-01]
 ..., 
 [ -1.84025671e-01  -2.37402009e-01  -3.83146843e-01 ...,   9.14337941e-02
   -6.00212321e-01  -3.23818612e-01]
 [ -2.74832831e-01  -1.80846827e-01  -1.79617860e-01 ...,  -1.17034900e-01
   -1.39632335e-01  -3.51550665e-01]
 [  3.89484150e-02   8.35117435e-02  -4.16745105e-02 ...,   5.30395381e-02
    2.90604823e+00  -7.65081417e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16197741]
 [-0.95267198]
 [-1.19738033]
 [-0.76544036]
 [-0.06019596]
 [ 2.64985351]
 [-0.05166541]
 [-1.09804248]
 [-0.53235604]
 [ 1.02442325]
 [-0.09472443]
 [ 0.14012134]
 [-0.10171815]
 [-1.00468227]
 [-0.30465652]
 [ 0.86731264]
 [-0.837285  ]
 [-0.79826756]
 [-0.62514092]
 [ 0.13851151]
 [-0.35308559]
 [ 4.48491796]
 [-0.9472546 ]
 [-1.65080477]
 [ 0.38249416]
 [-0.30665439]
 [ 4.31369069]
 [-1.91942644]]
[[ -1.91718310e-02  -3.07644473e-01   2.63465366e-01 ...,  -2.32816760e-01
   -3.31067814e-01   2.79101653e-01]
 [  5.82505778e-02   1.44797102e-01  -1.91988300e-03 ...,  -2.22501936e-01
    1.62073214e+00   1.13302411e-01]
 [ -6.03744824e-02   2.62162624e-01   4.66939690e-01 ...,   2.37340205e-01
   -3.04023792e-01   9.56282157e-01]
 ..., 
 [ -1.84029926e-01  -2.37419062e-01  -3.83240583e-01 ...,   9.14286983e-02
   -6.00334694e-01  -3.24003260e-01]
 [ -2.74865885e-01  -1.81030316e-01  -1.79633509e-01 ...,  -1.17090758e-01
   -1.39881655e-01  -3.51403868e-01]
 [  3.88512296e-02   8.29072825e-02  -4.22975242e-02 ...,   5.28529611e-02
    2.90621211e+00  -7.73153073e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16119959]
 [-0.95248876]
 [-1.19490389]
 [-0.76619832]
 [-0.06047801]
 [ 2.64937417]
 [-0.05176405]
 [-1.09852927]
 [-0.53081632]
 [ 1.02686358]
 [-0.09427918]
 [ 0.14095307]
 [-0.10129744]
 [-1.0050042 ]
 [-0.30403425]
 [ 0.86896367]
 [-0.83620551]
 [-0.79607175]
 [-0.62305975]
 [ 0.13860611]
 [-0.35155673]
 [ 4.48511898]
 [-0.94896333]
 [-1.65000131]
 [ 0.38286003]
 [-0.30658137]
 [ 4.31370813]
 [-1.9195056 ]]
[[ -1.91905051e-02  -3.07732583e-01   2.63355984e-01 ...,  -2.32845999e-01
   -3.30512684e-01   2.79041160e-01]
 [  5.82187791e-02   1.44609974e-01  -2.15192747e-03 ...,  -2.22558518e-01
    1.62135450e+00   1.12933957e-01]
 [ -6.04143219e-02   2.61939382e-01   4.67043522e-01 ...,   2.37256086e-01
   -3.03261605e-01   9.56200927e-01]
 ..., 
 [ -1.84048118e-01  -2.37511875e-01  -3.83376362e-01 ...,   9.13862851e-02
   -6.00190616e-01  -3.23902560e-01]
 [ -2.74850989e-01  -1.80960259e-01  -1.79621614e-01 ...,  -1.17053756e-01
   -1.40793387e-01  -3.51284248e-01]
 [  3.89547254e-02   8.35113764e-02  -4.18550534e-02 ...,   5.30536248e-02
    2.90601475e+00  -7.67365964e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16398245]
 [-0.95587198]
 [-1.19725031]
 [-0.76918415]
 [-0.06275558]
 [ 2.64562524]
 [-0.05516749]
 [-1.09959252]
 [-0.53378695]
 [ 1.02629979]
 [-0.09667746]
 [ 0.13842047]
 [-0.10516485]
 [-1.00915257]
 [-0.30698442]
 [ 0.86590706]
 [-0.83909162]
 [-0.79747318]
 [-0.62518544]
 [ 0.13616165]
 [-0.35392368]
 [ 4.48397863]
 [-0.95194541]
 [-1.65118711]
 [ 0.37992255]
 [-0.30980289]
 [ 4.30872941]
 [-1.92284414]]
[[ -1.89338450e-02  -3.06141591e-01   2.64882377e-01 ...,  -2.32356414e-01
   -3.33010814e-01   2.82225496e-01]
 [  5.83125251e-02   1.45167869e-01  -1.67324807e-03 ...,  -2.22384087e-01
    1.62073062e+00   1.13703422e-01]
 [ -6.00426910e-02   2.64113356e-01   4.69584426e-01 ...,   2.37959145e-01
   -3.08694987e-01   9.59902178e-01]
 ..., 
 [ -1.84020888e-01  -2.37396677e-01  -3.83345880e-01 ...,   9.14419343e-02
   -5.99693248e-01  -3.24259511e-01]
 [ -2.74780183e-01  -1.80543666e-01  -1.79048236e-01 ...,  -1.16929495e-01
   -1.42620854e-01  -3.50205892e-01]
 [  3.89323104e-02   8.33867913e-02  -4.21481525e-02 ...,   5.29961491e-02
    2.90599404e+00  -7.68337196e-02]]
Progress: 80.5% ... Training loss: 0.064 ... Validation loss: 0.137[[-0.16010463]
 [-0.95096289]
 [-1.19343162]
 [-0.76503243]
 [-0.05929221]
 [ 2.64844324]
 [-0.05111963]
 [-1.09739024]
 [-0.5283755 ]
 [ 1.02967859]
 [-0.09337011]
 [ 0.1421996 ]
 [-0.10006709]
 [-1.00511551]
 [-0.3025356 ]
 [ 0.87021683]
 [-0.83470983]
 [-0.79376054]
 [-0.62115495]
 [ 0.14007462]
 [-0.35003419]
 [ 4.48366778]
 [-0.94872426]
 [-1.64890774]
 [ 0.38352374]
 [-0.30511613]
 [ 4.31558044]
 [-1.91978422]]
[[ -1.89890146e-02  -3.06378601e-01   2.64712288e-01 ...,  -2.32438777e-01
   -3.29603382e-01   2.81150311e-01]
 [  5.82878494e-02   1.45021676e-01  -1.81195838e-03 ...,  -2.22429046e-01
    1.62078751e+00   1.13641635e-01]
 [ -6.04042563e-02   2.62159037e-01   4.67217708e-01 ...,   2.37328959e-01
   -3.07079980e-01   9.56620557e-01]
 ..., 
 [ -1.84129559e-01  -2.38004890e-01  -3.84087798e-01 ...,   9.12498761e-02
   -5.97917548e-01  -3.25077437e-01]
 [ -2.74892072e-01  -1.81145193e-01  -1.79587720e-01 ...,  -1.17131209e-01
   -1.40947337e-01  -3.50862442e-01]
 [  3.88904689e-02   8.31387709e-02  -4.23935908e-02 ...,   5.29166807e-02
    2.90608019e+00  -7.74421997e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.1617105 ]
 [-0.9519735 ]
 [-1.19388337]
 [-0.76687424]
 [-0.05982382]
 [ 2.64802971]
 [-0.05198037]
 [-1.09812819]
 [-0.52953454]
 [ 1.02926203]
 [-0.09419423]
 [ 0.14161457]
 [-0.1011974 ]
 [-1.00704681]
 [-0.30289276]
 [ 0.86975798]
 [-0.83590716]
 [-0.79502204]
 [-0.62121953]
 [ 0.1389017 ]
 [-0.35125684]
 [ 4.48374318]
 [-0.95086393]
 [-1.65006262]
 [ 0.38306371]
 [-0.30594769]
 [ 4.31402331]
 [-1.92122722]]
[[ -1.89645309e-02  -3.06159862e-01   2.64832258e-01 ...,  -2.32380907e-01
   -3.31241022e-01   2.81741285e-01]
 [  5.82978864e-02   1.45070537e-01  -1.71298279e-03 ...,  -2.22411130e-01
    1.62073842e+00   1.13695060e-01]
 [ -6.03459770e-02   2.62528284e-01   4.67304439e-01 ...,   2.37454645e-01
   -3.09411402e-01   9.57485235e-01]
 ..., 
 [ -1.84100063e-01  -2.37819069e-01  -3.83920380e-01 ...,   9.13068270e-02
   -5.98235204e-01  -3.24718613e-01]
 [ -2.74922302e-01  -1.81325089e-01  -1.79903160e-01 ...,  -1.17188659e-01
   -1.39813585e-01  -3.51307400e-01]
 [  3.88725147e-02   8.30242640e-02  -4.25788862e-02 ...,   5.28827622e-02
    2.90618921e+00  -7.77011351e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16114768]
 [-0.9519226 ]
 [-1.19425662]
 [-0.766019  ]
 [-0.06021471]
 [ 2.64906282]
 [-0.05126906]
 [-1.09831622]
 [-0.52892428]
 [ 1.02866352]
 [-0.09435743]
 [ 0.14131727]
 [-0.10064976]
 [-1.00566943]
 [-0.302958  ]
 [ 0.86896463]
 [-0.83570406]
 [-0.79510538]
 [-0.62173231]
 [ 0.13906641]
 [-0.35150472]
 [ 4.48317713]
 [-0.94952833]
 [-1.65012849]
 [ 0.38313235]
 [-0.30547532]
 [ 4.31433659]
 [-1.92030299]]
[[ -1.89841236e-02  -3.06285511e-01   2.64800223e-01 ...,  -2.32424902e-01
   -3.29781305e-01   2.81660441e-01]
 [  5.82807575e-02   1.44981156e-01  -1.75861202e-03 ...,  -2.22445495e-01
    1.62089136e+00   1.13593602e-01]
 [ -6.04398477e-02   2.62023892e-01   4.66314533e-01 ...,   2.37321883e-01
   -3.06524046e-01   9.55916319e-01]
 ..., 
 [ -1.84169261e-01  -2.38225107e-01  -3.84623200e-01 ...,   9.11915991e-02
   -5.96299967e-01  -3.25729963e-01]
 [ -2.74903638e-01  -1.81223689e-01  -1.79933232e-01 ...,  -1.17154925e-01
   -1.39399114e-01  -3.51168415e-01]
 [  3.88932804e-02   8.31451247e-02  -4.26170836e-02 ...,   5.29257415e-02
    2.90616100e+00  -7.76494277e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16190846]
 [-0.95217972]
 [-1.1954441 ]
 [-0.76588004]
 [-0.05966059]
 [ 2.64934487]
 [-0.05107886]
 [-1.09840415]
 [-0.52968907]
 [ 1.02791375]
 [-0.09436081]
 [ 0.14073483]
 [-0.10097276]
 [-1.00575349]
 [-0.30329533]
 [ 0.86831587]
 [-0.83662873]
 [-0.79678706]
 [-0.62268434]
 [ 0.13887809]
 [-0.35289289]
 [ 4.48342104]
 [-0.94919685]
 [-1.65101295]
 [ 0.38271237]
 [-0.30506965]
 [ 4.3126417 ]
 [-1.92032727]]
[[ -1.89998494e-02  -3.06315282e-01   2.64747131e-01 ...,  -2.32457852e-01
   -3.28121501e-01   2.81917570e-01]
 [  5.82863537e-02   1.45006293e-01  -1.72425071e-03 ...,  -2.22436181e-01
    1.62085879e+00   1.13641602e-01]
 [ -6.04724325e-02   2.61855088e-01   4.65741807e-01 ...,   2.37270189e-01
   -3.04854413e-01   9.55226483e-01]
 ..., 
 [ -1.84169871e-01  -2.38211505e-01  -3.84829562e-01 ...,   9.11905182e-02
   -5.96215429e-01  -3.25862692e-01]
 [ -2.74855767e-01  -1.80953798e-01  -1.79726365e-01 ...,  -1.17072112e-01
   -1.40480094e-01  -3.50888204e-01]
 [  3.89526891e-02   8.35071569e-02  -4.22025619e-02 ...,   5.30438372e-02
    2.90606412e+00  -7.68414074e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15940866]
 [-0.95042352]
 [-1.19253663]
 [-0.76494042]
 [-0.05831045]
 [ 2.64993242]
 [-0.04930269]
 [-1.09626058]
 [-0.52785773]
 [ 1.03063875]
 [-0.0924653 ]
 [ 0.14348903]
 [-0.09868312]
 [-1.00476807]
 [-0.30110897]
 [ 0.87154463]
 [-0.83399358]
 [-0.79305908]
 [-0.62041268]
 [ 0.14130943]
 [-0.35019673]
 [ 4.48435527]
 [-0.94789574]
 [-1.64721423]
 [ 0.38440237]
 [-0.30345961]
 [ 4.31741373]
 [-1.92007286]]
[[ -1.91972752e-02  -3.07474318e-01   2.63906907e-01 ...,  -2.32840786e-01
   -3.26276150e-01   2.81110680e-01]
 [  5.82805493e-02   1.44973211e-01  -1.74859305e-03 ...,  -2.22445644e-01
    1.62089201e+00   1.13603648e-01]
 [ -6.03744004e-02   2.62340862e-01   4.66274042e-01 ...,   2.37439518e-01
   -3.07855464e-01   9.56057928e-01]
 ..., 
 [ -1.84155833e-01  -2.38098298e-01  -3.84873002e-01 ...,   9.12227268e-02
   -5.96612023e-01  -3.25666819e-01]
 [ -2.74914828e-01  -1.81309946e-01  -1.80034947e-01 ...,  -1.17187310e-01
   -1.39779395e-01  -3.51244291e-01]
 [  3.89636768e-02   8.35885319e-02  -4.20885105e-02 ...,   5.30671364e-02
    2.90598506e+00  -7.65968685e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16079301]
 [-0.95130862]
 [-1.19349819]
 [-0.76612027]
 [-0.06017366]
 [ 2.65046727]
 [-0.05043594]
 [-1.09807777]
 [-0.52901643]
 [ 1.02926787]
 [-0.09352738]
 [ 0.14216681]
 [-0.1002041 ]
 [-1.00549122]
 [-0.30232869]
 [ 0.87009636]
 [-0.8350989 ]
 [-0.79461627]
 [-0.62140335]
 [ 0.14001156]
 [-0.35118887]
 [ 4.484356  ]
 [-0.94898337]
 [-1.6491461 ]
 [ 0.38373375]
 [-0.30474634]
 [ 4.31603015]
 [-1.92024967]]
[[ -1.91959545e-02  -3.07524697e-01   2.63903936e-01 ...,  -2.32850555e-01
   -3.29259590e-01   2.80842844e-01]
 [  5.82943565e-02   1.45054014e-01  -1.72449265e-03 ...,  -2.22420269e-01
    1.62085768e+00   1.13646152e-01]
 [ -6.04828923e-02   2.61747370e-01   4.65651047e-01 ...,   2.37256554e-01
   -3.10521081e-01   9.55875306e-01]
 ..., 
 [ -1.84152898e-01  -2.38078664e-01  -3.84810103e-01 ...,   9.12320234e-02
   -5.97260426e-01  -3.25523445e-01]
 [ -2.74917495e-01  -1.81310166e-01  -1.80139091e-01 ...,  -1.17199599e-01
   -1.39796798e-01  -3.51577911e-01]
 [  3.90368593e-02   8.40446190e-02  -4.18343363e-02 ...,   5.31842238e-02
    2.90602442e+00  -7.63208641e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.1658758 ]
 [-0.95632543]
 [-1.19729678]
 [-0.77068997]
 [-0.0638182 ]
 [ 2.64644275]
 [-0.05585052]
 [-1.10100476]
 [-0.53293026]
 [ 1.02718311]
 [-0.09762767]
 [ 0.13780032]
 [-0.10574834]
 [-1.00999804]
 [-0.30736107]
 [ 0.86531551]
 [-0.84034166]
 [-0.79893041]
 [-0.62475143]
 [ 0.13609675]
 [-0.35545307]
 [ 4.48307387]
 [-0.95378474]
 [-1.65286379]
 [ 0.3791975 ]
 [-0.30902831]
 [ 4.30672052]
 [-1.92325463]]
[[ -1.89387265e-02  -3.05952250e-01   2.65302994e-01 ...,  -2.32365011e-01
   -3.31713418e-01   2.83156175e-01]
 [  5.83508629e-02   1.45408083e-01  -1.67131232e-03 ...,  -2.22315609e-01
    1.62064543e+00   1.14257437e-01]
 [ -6.01999038e-02   2.63299145e-01   4.67376452e-01 ...,   2.37778265e-01
   -3.11515080e-01   9.58243482e-01]
 ..., 
 [ -1.84155929e-01  -2.38087647e-01  -3.85230313e-01 ...,   9.12289250e-02
   -5.96556509e-01  -3.25302885e-01]
 [ -2.74753686e-01  -1.80379746e-01  -1.79195844e-01 ...,  -1.16896215e-01
   -1.40706499e-01  -3.50205336e-01]
 [  3.90529167e-02   8.41419995e-02  -4.18449284e-02 ...,   5.32031007e-02
    2.90607480e+00  -7.64879781e-02]]
Progress: 80.5% ... Training loss: 0.065 ... Validation loss: 0.136[[-0.15933432]
 [-0.95149912]
 [-1.19269552]
 [-0.76430902]
 [-0.0585672 ]
 [ 2.64985558]
 [-0.05003092]
 [-1.09677318]
 [-0.52742179]
 [ 1.02988704]
 [-0.09148815]
 [ 0.14266497]
 [-0.10024386]
 [-1.00476807]
 [-0.30185154]
 [ 0.87086226]
 [-0.83420978]
 [-0.79495536]
 [-0.62077947]
 [ 0.14082771]
 [-0.35145759]
 [ 4.48437501]
 [-0.94716082]
 [-1.64846339]
 [ 0.38383457]
 [-0.30381575]
 [ 4.31625929]
 [-1.91977542]]
[[ -1.91539785e-02  -3.07142840e-01   2.63975106e-01 ...,  -2.32752366e-01
   -3.27802827e-01   2.81072016e-01]
 [  5.83309714e-02   1.45284887e-01  -1.88251111e-03 ...,  -2.22350886e-01
    1.62208531e+00   1.13878126e-01]
 [ -6.03974441e-02   2.62102917e-01   4.64966787e-01 ...,   2.37428299e-01
   -3.06799929e-01   9.54109068e-01]
 ..., 
 [ -1.84179177e-01  -2.38210210e-01  -3.85444108e-01 ...,   9.11762857e-02
   -5.95585715e-01  -3.25628486e-01]
 [ -2.74830349e-01  -1.80806745e-01  -1.79459832e-01 ...,  -1.17027794e-01
   -1.40046085e-01  -3.50804815e-01]
 [  3.90292894e-02   8.39950210e-02  -4.20149479e-02 ...,   5.31540523e-02
    2.90607196e+00  -7.66736254e-02]]
Progress: 80.5% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15835301]
 [-0.9508035 ]
 [-1.19071997]
 [-0.76476291]
 [-0.05889233]
 [ 2.6503461 ]
 [-0.04966336]
 [-1.09681144]
 [-0.5260829 ]
 [ 1.03105695]
 [-0.09108489]
 [ 0.14381546]
 [-0.0996605 ]
 [-1.00383225]
 [-0.30132645]
 [ 0.87249355]
 [-0.8336404 ]
 [-0.79316334]
 [-0.61915796]
 [ 0.14173698]
 [-0.34986519]
 [ 4.48423355]
 [-0.94658357]
 [-1.64652719]
 [ 0.38480609]
 [-0.30375518]
 [ 4.31769609]
 [-1.91916294]]
[[ -1.92881114e-02  -3.07809030e-01   2.63502457e-01 ...,  -2.32976775e-01
   -3.25725682e-01   2.79857542e-01]
 [  5.82773760e-02   1.44976648e-01  -2.12447382e-03 ...,  -2.22447064e-01
    1.62238504e+00   1.13556828e-01]
 [ -6.04124196e-02   2.61955615e-01   4.65136436e-01 ...,   2.37406533e-01
   -3.07692356e-01   9.54106082e-01]
 ..., 
 [ -1.84343985e-01  -2.39158468e-01  -3.86431410e-01 ...,   9.08804199e-02
   -5.93894976e-01  -3.27214116e-01]
 [ -2.74852268e-01  -1.80944134e-01  -1.79546219e-01 ...,  -1.17069468e-01
   -1.40167283e-01  -3.50994648e-01]
 [  3.90207040e-02   8.39783658e-02  -4.19994671e-02 ...,   5.31416661e-02
    2.90607918e+00  -7.68331062e-02]]
Progress: 80.5% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16093527]
 [-0.95242379]
 [-1.19365807]
 [-0.7661269 ]
 [-0.06098462]
 [ 2.65163886]
 [-0.05062888]
 [-1.09851043]
 [-0.52848174]
 [ 1.02855239]
 [-0.09290228]
 [ 0.14166472]
 [-0.10176339]
 [-1.00439773]
 [-0.30353446]
 [ 0.870007  ]
 [-0.83648098]
 [-0.79663885]
 [-0.62210964]
 [ 0.13949781]
 [-0.35246861]
 [ 4.48406234]
 [-0.94765337]
 [-1.6505064 ]
 [ 0.38400328]
 [-0.30514295]
 [ 4.31362334]
 [-1.9198833 ]]
[[ -1.92160764e-02  -3.07460606e-01   2.64236109e-01 ...,  -2.32855921e-01
   -3.26301172e-01   2.80493142e-01]
 [  5.82634521e-02   1.44891881e-01  -2.26663178e-03 ...,  -2.22469593e-01
    1.62312008e+00   1.13326287e-01]
 [ -6.05280982e-02   2.61326131e-01   4.64172385e-01 ...,   2.37213400e-01
   -3.07678372e-01   9.53683207e-01]
 ..., 
 [ -1.84323485e-01  -2.39062327e-01  -3.86223014e-01 ...,   9.09092230e-02
   -5.94241434e-01  -3.27123410e-01]
 [ -2.74840220e-01  -1.80896549e-01  -1.79343546e-01 ...,  -1.17054786e-01
   -1.40151779e-01  -3.50779222e-01]
 [  3.90488061e-02   8.41434223e-02  -4.17848038e-02 ...,   5.31948701e-02
    2.90602152e+00  -7.66379692e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16542327]
 [-0.95611477]
 [-1.1979489 ]
 [-0.76905716]
 [-0.06387315]
 [ 2.65100635]
 [-0.05393908]
 [-1.10171339]
 [-0.5323283 ]
 [ 1.02470451]
 [-0.09662731]
 [ 0.13794984]
 [-0.1053477 ]
 [-1.00623069]
 [-0.30758747]
 [ 0.86536435]
 [-0.84112661]
 [-0.80172315]
 [-0.62647413]
 [ 0.13622875]
 [-0.35722837]
 [ 4.48273395]
 [-0.95013107]
 [-1.65558556]
 [ 0.38089224]
 [-0.3082439 ]
 [ 4.30554306]
 [-1.92119224]]
[[ -1.90524480e-02  -3.06445466e-01   2.65126853e-01 ...,  -2.32552300e-01
   -3.25836118e-01   2.81152722e-01]
 [  5.82634521e-02   1.44891881e-01  -2.26663178e-03 ...,  -2.22469593e-01
    1.62312008e+00   1.13326287e-01]
 [ -6.05594933e-02   2.61257806e-01   4.63998240e-01 ...,   2.37168309e-01
   -3.04903686e-01   9.53568917e-01]
 ..., 
 [ -1.84302370e-01  -2.38935783e-01  -3.86268694e-01 ...,   9.09498703e-02
   -5.93877414e-01  -3.27098460e-01]
 [ -2.74772687e-01  -1.80448184e-01  -1.78857264e-01 ...,  -1.16920076e-01
   -1.39608287e-01  -3.50356003e-01]
 [  3.91352740e-02   8.46515141e-02  -4.12189896e-02 ...,   5.33527220e-02
    2.90595997e+00  -7.58984820e-02]]
Progress: 80.6% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16021439]
 [-0.95207823]
 [-1.19457668]
 [-0.76507777]
 [-0.05881968]
 [ 2.65215637]
 [-0.04993529]
 [-1.09782229]
 [-0.52805832]
 [ 1.02878749]
 [-0.09197548]
 [ 0.1427318 ]
 [-0.10051531]
 [-1.0034082 ]
 [-0.30256862]
 [ 0.87141181]
 [-0.83683805]
 [-0.79712819]
 [-0.62212738]
 [ 0.14156674]
 [-0.35199219]
 [ 4.48382755]
 [-0.94625003]
 [-1.65042977]
 [ 0.38437864]
 [-0.30448723]
 [ 4.31307437]
 [-1.91987781]]
[[ -1.92163881e-02  -3.07405781e-01   2.64235988e-01 ...,  -2.32838110e-01
   -3.22378084e-01   2.79959516e-01]
 [  5.82609299e-02   1.44887798e-01  -2.44647239e-03 ...,  -2.22475901e-01
    1.62373848e+00   1.13086015e-01]
 [ -6.04748756e-02   2.61540863e-01   4.64318379e-01 ...,   2.37286089e-01
   -3.01676807e-01   9.53147208e-01]
 ..., 
 [ -1.84313498e-01  -2.38993678e-01  -3.86493856e-01 ...,   9.09200683e-02
   -5.93765146e-01  -3.27277425e-01]
 [ -2.74829893e-01  -1.80798177e-01  -1.79047066e-01 ...,  -1.17026518e-01
   -1.38161826e-01  -3.50620259e-01]
 [  3.91964628e-02   8.49512246e-02  -4.06517918e-02 ...,   5.34700127e-02
    2.90585252e+00  -7.49358898e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16443623]
 [-0.95552676]
 [-1.19936023]
 [-0.76657411]
 [-0.06094326]
 [ 2.64969027]
 [-0.05265719]
 [-1.09876529]
 [-0.53242982]
 [ 1.02629322]
 [-0.09398763]
 [ 0.13981601]
 [-0.10344093]
 [-1.00546583]
 [-0.3069562 ]
 [ 0.86742712]
 [-0.8414778 ]
 [-0.80165069]
 [-0.62636616]
 [ 0.13889152]
 [-0.35551549]
 [ 4.48410379]
 [-0.94758323]
 [-1.65370921]
 [ 0.38103766]
 [-0.30697951]
 [ 4.30574533]
 [-1.92181797]]
[[ -1.90502465e-02  -3.06376758e-01   2.65422521e-01 ...,  -2.32539039e-01
   -3.22761648e-01   2.81628665e-01]
 [  5.82516094e-02   1.44820237e-01  -2.62794656e-03 ...,  -2.22493240e-01
    1.62370192e+00   1.13010720e-01]
 [ -6.02294859e-02   2.62953481e-01   4.65943350e-01 ...,   2.37711845e-01
   -3.00020685e-01   9.55379958e-01]
 ..., 
 [ -1.84391388e-01  -2.39455444e-01  -3.86823111e-01 ...,   9.07735493e-02
   -5.91981884e-01  -3.27769929e-01]
 [ -2.74831326e-01  -1.80802646e-01  -1.79034081e-01 ...,  -1.17024122e-01
   -1.37670387e-01  -3.50774455e-01]
 [  3.93455141e-02   8.58859735e-02  -3.96928500e-02 ...,   5.37623867e-02
    2.90555217e+00  -7.34477199e-02]]
Progress: 80.6% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16354665]
 [-0.95615605]
 [-1.19847153]
 [-0.76581313]
 [-0.05973274]
 [ 2.64678069]
 [-0.05315478]
 [-1.09602032]
 [-0.53311494]
 [ 1.02768242]
 [-0.09331688]
 [ 0.14059106]
 [-0.10376356]
 [-1.00825085]
 [-0.30682074]
 [ 0.86876919]
 [-0.84064128]
 [-0.80056442]
 [-0.62531431]
 [ 0.13902012]
 [-0.35443241]
 [ 4.4842592 ]
 [-0.94803569]
 [-1.64961244]
 [ 0.38026133]
 [-0.30713991]
 [ 4.30652864]
 [-1.92376668]]
[[ -1.90317816e-02  -3.06180766e-01   2.65459155e-01 ...,  -2.32489175e-01
   -3.23713150e-01   2.82759230e-01]
 [  5.82548837e-02   1.44822018e-01  -2.53144375e-03 ...,  -2.22487692e-01
    1.62369746e+00   1.13168667e-01]
 [ -5.98048343e-02   2.65249119e-01   4.68435716e-01 ...,   2.38481004e-01
   -3.02991419e-01   9.59037958e-01]
 ..., 
 [ -1.84366348e-01  -2.39300828e-01  -3.86657482e-01 ...,   9.08205531e-02
   -5.92757526e-01  -3.27378640e-01]
 [ -2.74808616e-01  -1.80691214e-01  -1.79067328e-01 ...,  -1.16981895e-01
   -1.37802006e-01  -3.50687628e-01]
 [  3.94034564e-02   8.61881966e-02  -3.94267000e-02 ...,   5.38677026e-02
    2.90536326e+00  -7.25725176e-02]]
Progress: 80.6% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16037743]
 [-0.95280017]
 [-1.19514527]
 [-0.76305644]
 [-0.05679004]
 [ 2.64879332]
 [-0.05031531]
 [-1.09401675]
 [-0.52942595]
 [ 1.0301813 ]
 [-0.09074511]
 [ 0.14417776]
 [-0.09954421]
 [-1.00581979]
 [-0.30301191]
 [ 0.87270103]
 [-0.83674825]
 [-0.79668378]
 [-0.62215496]
 [ 0.14274271]
 [-0.35108035]
 [ 4.48452286]
 [-0.94540294]
 [-1.64628592]
 [ 0.38310538]
 [-0.30393013]
 [ 4.31240944]
 [-1.92211274]]
[[ -1.91940777e-02  -3.07060017e-01   2.64559537e-01 ...,  -2.32800510e-01
   -3.21410859e-01   2.81960351e-01]
 [  5.83292175e-02   1.45287008e-01  -1.98438578e-03 ...,  -2.22361111e-01
    1.62367710e+00   1.14076107e-01]
 [ -5.99421338e-02   2.64512448e-01   4.67827745e-01 ...,   2.38210792e-01
   -3.00012399e-01   9.57429154e-01]
 ..., 
 [ -1.84371226e-01  -2.39320670e-01  -3.86701123e-01 ...,   9.08096125e-02
   -5.92499134e-01  -3.27323812e-01]
 [ -2.74927845e-01  -1.81370940e-01  -1.79715407e-01 ...,  -1.17207406e-01
   -1.36984910e-01  -3.51747997e-01]
 [  3.93110956e-02   8.56549287e-02  -4.00050322e-02 ...,   5.37067772e-02
    2.90553095e+00  -7.34111822e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.143[[-0.16307127]
 [-0.95696197]
 [-1.19913931]
 [-0.76535014]
 [-0.05983072]
 [ 2.64708405]
 [-0.05332365]
 [-1.09535449]
 [-0.53407424]
 [ 1.02781015]
 [-0.09334103]
 [ 0.14092617]
 [-0.1034561 ]
 [-1.00862845]
 [-0.30727698]
 [ 0.86854895]
 [-0.84048172]
 [-0.79873861]
 [-0.62671437]
 [ 0.1390275 ]
 [-0.35428262]
 [ 4.48289786]
 [-0.94563262]
 [-1.64747005]
 [ 0.38056493]
 [-0.30830593]
 [ 4.30779787]
 [-1.92471199]]
[[ -1.90025586e-02  -3.05954087e-01   2.65819013e-01 ...,  -2.32418698e-01
   -3.24447345e-01   2.84400882e-01]
 [  5.82947410e-02   1.45083357e-01  -2.24541869e-03 ...,  -2.22421203e-01
    1.62401251e+00   1.13840859e-01]
 [ -5.95976356e-02   2.66483775e-01   4.69925005e-01 ...,   2.38848720e-01
   -3.03831564e-01   9.60670602e-01]
 ..., 
 [ -1.84299021e-01  -2.38910313e-01  -3.86210364e-01 ...,   9.09500775e-02
   -5.94380286e-01  -3.26740145e-01]
 [ -2.74941772e-01  -1.81465154e-01  -1.79749376e-01 ...,  -1.17223222e-01
   -1.36641205e-01  -3.51724794e-01]
 [  3.93273862e-02   8.57387787e-02  -3.97190206e-02 ...,   5.37405347e-02
    2.90562018e+00  -7.28228564e-02]]
Progress: 80.6% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15843449]
 [-0.95260203]
 [-1.19451076]
 [-0.76191798]
 [-0.05598774]
 [ 2.6490645 ]
 [-0.04984511]
 [-1.09212436]
 [-0.53013341]
 [ 1.03077776]
 [-0.08969557]
 [ 0.14508346]
 [-0.09876642]
 [-1.00583748]
 [-0.30261436]
 [ 0.87328727]
 [-0.83548174]
 [-0.79422883]
 [-0.62248407]
 [ 0.14303258]
 [-0.3497877 ]
 [ 4.48343048]
 [-0.94268575]
 [-1.64208026]
 [ 0.38380535]
 [-0.30498024]
 [ 4.31541658]
 [-1.922564  ]]
[[ -1.92851125e-02  -3.07508435e-01   2.64299379e-01 ...,  -2.32914195e-01
   -3.22262801e-01   2.82561018e-01]
 [  5.82343956e-02   1.44781457e-01  -2.47029390e-03 ...,  -2.22521771e-01
    1.62436971e+00   1.13655561e-01]
 [ -5.96376369e-02   2.66208180e-01   4.69336331e-01 ...,   2.38764919e-01
   -3.03962153e-01   9.58678617e-01]
 ..., 
 [ -1.84261805e-01  -2.38693230e-01  -3.86040729e-01 ...,   9.10223353e-02
   -5.95066991e-01  -3.26378841e-01]
 [ -2.74909528e-01  -1.81257568e-01  -1.79409782e-01 ...,  -1.17156326e-01
   -1.36661419e-01  -3.51316730e-01]
 [  3.91914571e-02   8.49548297e-02  -4.04226311e-02 ...,   5.34936052e-02
    2.90575633e+00  -7.40963417e-02]]
Progress: 80.6% ... Training loss: 0.062 ... Validation loss: 0.146[[-0.16227521]
 [-0.95511376]
 [-1.1960877 ]
 [-0.76511642]
 [-0.05931541]
 [ 2.64685439]
 [-0.05281801]
 [-1.09526935]
 [-0.53315395]
 [ 1.02992852]
 [-0.09260311]
 [ 0.1415229 ]
 [-0.10219279]
 [-1.00855983]
 [-0.30565254]
 [ 0.86880913]
 [-0.83824623]
 [-0.79630886]
 [-0.62549906]
 [ 0.13918138]
 [-0.35363893]
 [ 4.48373853]
 [-0.94543117]
 [-1.64580464]
 [ 0.3805023 ]
 [-0.30781938]
 [ 4.31096979]
 [-1.92467328]]
[[ -1.89798549e-02  -3.05829806e-01   2.66167599e-01 ...,  -2.32355980e-01
   -3.26937965e-01   2.85486508e-01]
 [  5.82492363e-02   1.44870160e-01  -2.44290380e-03 ...,  -2.22493254e-01
    1.62430274e+00   1.13707048e-01]
 [ -5.96514469e-02   2.66117799e-01   4.69645807e-01 ...,   2.38746666e-01
   -3.04592132e-01   9.59332433e-01]
 ..., 
 [ -1.84247586e-01  -2.38629341e-01  -3.86175106e-01 ...,   9.10500827e-02
   -5.95968221e-01  -3.26556476e-01]
 [ -2.74889990e-01  -1.81160698e-01  -1.79325588e-01 ...,  -1.17117746e-01
   -1.36776707e-01  -3.51133618e-01]
 [  3.91934793e-02   8.50058964e-02  -4.02104962e-02 ...,   5.35007188e-02
    2.90569593e+00  -7.37616369e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16103285]
 [-0.95350151]
 [-1.19472484]
 [-0.7634009 ]
 [-0.05779258]
 [ 2.64792774]
 [-0.05099517]
 [-1.09457182]
 [-0.53152792]
 [ 1.03092922]
 [-0.09134169]
 [ 0.14279116]
 [-0.09988608]
 [-1.00746991]
 [-0.30430268]
 [ 0.87118622]
 [-0.83656614]
 [-0.79524286]
 [-0.62413537]
 [ 0.14035223]
 [-0.35214763]
 [ 4.48604745]
 [-0.94504523]
 [-1.64517908]
 [ 0.38174729]
 [-0.30565595]
 [ 4.31331649]
 [-1.92386544]]
[[ -1.90701956e-02  -3.06394369e-01   2.65748728e-01 ...,  -2.32517732e-01
   -3.25031059e-01   2.84218126e-01]
 [  5.82589989e-02   1.44918328e-01  -2.39597025e-03 ...,  -2.22476235e-01
    1.62426475e+00   1.13766229e-01]
 [ -5.97738377e-02   2.65403708e-01   4.69166481e-01 ...,   2.38545895e-01
   -3.02300918e-01   9.58415529e-01]
 ..., 
 [ -1.84244921e-01  -2.38644745e-01  -3.86141690e-01 ...,   9.10535800e-02
   -5.95586571e-01  -3.26630185e-01]
 [ -2.74998767e-01  -1.81834724e-01  -1.80065521e-01 ...,  -1.17329297e-01
   -1.35388071e-01  -3.52667529e-01]
 [  3.92045405e-02   8.50571857e-02  -3.99389130e-02 ...,   5.35188648e-02
    2.90559449e+00  -7.35109271e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.143[[-0.1605729 ]
 [-0.95331689]
 [-1.1942464 ]
 [-0.76302977]
 [-0.05838563]
 [ 2.64768126]
 [-0.05143051]
 [-1.09465259]
 [-0.53075128]
 [ 1.03133395]
 [-0.0906488 ]
 [ 0.14253275]
 [-0.10093869]
 [-1.00727705]
 [-0.30457558]
 [ 0.87054408]
 [-0.83614883]
 [-0.79483439]
 [-0.62347943]
 [ 0.14022808]
 [-0.35206064]
 [ 4.48598514]
 [-0.94459499]
 [-1.64514895]
 [ 0.38180244]
 [-0.3058104 ]
 [ 4.31405893]
 [-1.92354827]]
[[ -1.90437266e-02  -3.06261724e-01   2.65902170e-01 ...,  -2.32450499e-01
   -3.25935921e-01   2.84801910e-01]
 [  5.82506221e-02   1.44868840e-01  -2.40412548e-03 ...,  -2.22491041e-01
    1.62426294e+00   1.13755895e-01]
 [ -5.98008323e-02   2.65293894e-01   4.69133786e-01 ...,   2.38502541e-01
   -3.02720626e-01   9.58090423e-01]
 ..., 
 [ -1.84322852e-01  -2.39096969e-01  -3.86611037e-01 ...,   9.09137172e-02
   -5.94441470e-01  -3.27415480e-01]
 [ -2.74899147e-01  -1.81307622e-01  -1.79500586e-01 ...,  -1.17139133e-01
   -1.36894184e-01  -3.51975610e-01]
 [  3.93247761e-02   8.57698235e-02  -3.91650104e-02 ...,   5.37429272e-02
    2.90532074e+00  -7.22367901e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.142[[-0.16029846]
 [-0.95223238]
 [-1.19267052]
 [-0.76258893]
 [-0.05733287]
 [ 2.6482715 ]
 [-0.05085671]
 [-1.09371647]
 [-0.52986479]
 [ 1.0318346 ]
 [-0.08990434]
 [ 0.14354574]
 [-0.10056962]
 [-1.00806423]
 [-0.3031269 ]
 [ 0.87264424]
 [-0.83513087]
 [-0.79459982]
 [-0.62154934]
 [ 0.14042955]
 [-0.35173136]
 [ 4.48553299]
 [-0.94558125]
 [-1.64445271]
 [ 0.38275687]
 [-0.3047741 ]
 [ 4.31531265]
 [-1.92417325]]
[[ -1.90241652e-02  -3.06092239e-01   2.66280608e-01 ...,  -2.32389273e-01
   -3.25845296e-01   2.85963201e-01]
 [  5.82359014e-02   1.44783712e-01  -2.52332132e-03 ...,  -2.22519943e-01
    1.62429071e+00   1.13672618e-01]
 [ -5.98448247e-02   2.65262315e-01   4.69002040e-01 ...,   2.38470159e-01
   -3.02980812e-01   9.58248930e-01]
 ..., 
 [ -1.84316500e-01  -2.39097616e-01  -3.86565906e-01 ...,   9.09205653e-02
   -5.94240695e-01  -3.27440734e-01]
 [ -2.74940506e-01  -1.81540480e-01  -1.79760730e-01 ...,  -1.17208776e-01
   -1.35892111e-01  -3.52369160e-01]
 [  3.92588750e-02   8.53829174e-02  -3.93224023e-02 ...,   5.36229734e-02
    2.90546129e+00  -7.25921381e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.142[[-0.16339093]
 [-0.95424273]
 [-1.19371516]
 [-0.76605386]
 [-0.06040891]
 [ 2.64746607]
 [-0.05340768]
 [-1.09726158]
 [-0.53135469]
 [ 1.0300334 ]
 [-0.09282539]
 [ 0.14122247]
 [-0.10339121]
 [-1.00935274]
 [-0.305278  ]
 [ 0.86969761]
 [-0.83745193]
 [-0.79623608]
 [-0.62252364]
 [ 0.13810993]
 [-0.35439561]
 [ 4.48408226]
 [-0.94810657]
 [-1.6482179 ]
 [ 0.38129426]
 [-0.30663987]
 [ 4.31014733]
 [-1.92495493]]
[[ -1.88800579e-02  -3.05239602e-01   2.67048861e-01 ...,  -2.32119491e-01
   -3.25717510e-01   2.87015488e-01]
 [  5.83038706e-02   1.45165793e-01  -2.00444915e-03 ...,  -2.22392591e-01
    1.62403356e+00   1.14450599e-01]
 [ -5.99971299e-02   2.64357451e-01   4.68272194e-01 ...,   2.38205198e-01
   -3.01499334e-01   9.57787088e-01]
 ..., 
 [ -1.84343939e-01  -2.39243908e-01  -3.86629466e-01 ...,   9.08681870e-02
   -5.93472372e-01  -3.27850044e-01]
 [ -2.74820610e-01  -1.80846893e-01  -1.79083864e-01 ...,  -1.17006669e-01
   -1.35580394e-01  -3.51488085e-01]
 [  3.91911748e-02   8.49890801e-02  -3.98864809e-02 ...,   5.35024193e-02
    2.90551585e+00  -7.31701069e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15866415]
 [-0.9503456 ]
 [-1.1891187 ]
 [-0.76275885]
 [-0.05737133]
 [ 2.64929265]
 [-0.04986558]
 [-1.09426952]
 [-0.52722923]
 [ 1.03284   ]
 [-0.08864041]
 [ 0.14543584]
 [-0.09899388]
 [-1.00659041]
 [-0.30082993]
 [ 0.87433442]
 [-0.8326524 ]
 [-0.79120515]
 [-0.61844535]
 [ 0.14234396]
 [-0.35008021]
 [ 4.48565907]
 [-0.94497586]
 [-1.64347214]
 [ 0.38471861]
 [-0.30313271]
 [ 4.31900348]
 [-1.92273076]]
[[ -1.91625656e-02  -3.06843180e-01   2.65567841e-01 ...,  -2.32637875e-01
   -3.24083958e-01   2.84601855e-01]
 [  5.82906529e-02   1.45088404e-01  -2.09897847e-03 ...,  -2.22411782e-01
    1.62406219e+00   1.14395939e-01]
 [ -6.00382216e-02   2.64132999e-01   4.68050997e-01 ...,   2.38143410e-01
   -3.02535986e-01   9.56978333e-01]
 ..., 
 [ -1.84444933e-01  -2.39809636e-01  -3.87182928e-01 ...,   9.06827930e-02
   -5.92463585e-01  -3.28822008e-01]
 [ -2.74914329e-01  -1.81398703e-01  -1.79640833e-01 ...,  -1.17162863e-01
   -1.34902138e-01  -3.52379577e-01]
 [  3.90531519e-02   8.42119433e-02  -4.05102718e-02 ...,   5.32434285e-02
    2.90585957e+00  -7.43209743e-02]]
Progress: 80.6% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16391417]
 [-0.95432175]
 [-1.19203945]
 [-0.76802451]
 [-0.06214255]
 [ 2.64846065]
 [-0.05411001]
 [-1.09999509]
 [-0.53122283]
 [ 1.02886716]
 [-0.09406008]
 [ 0.14074435]
 [-0.10276578]
 [-1.0087509 ]
 [-0.30495861]
 [ 0.86874887]
 [-0.83790319]
 [-0.79498565]
 [-0.62225684]
 [ 0.13821692]
 [-0.35405011]
 [ 4.48508426]
 [-0.94933156]
 [-1.6495573 ]
 [ 0.38142393]
 [-0.3069942 ]
 [ 4.31195576]
 [-1.92360465]]
[[ -1.91102645e-02  -3.06594289e-01   2.65923762e-01 ...,  -2.32535719e-01
   -3.26660320e-01   2.84164086e-01]
 [  5.82921232e-02   1.45096063e-01  -2.08885885e-03 ...,  -2.22409442e-01
    1.62405672e+00   1.14402484e-01]
 [ -6.01668883e-02   2.63348871e-01   4.67458994e-01 ...,   2.37910450e-01
   -3.05910799e-01   9.57173024e-01]
 ..., 
 [ -1.84368810e-01  -2.39379502e-01  -3.86709149e-01 ...,   9.08245579e-02
   -5.94204149e-01  -3.28093268e-01]
 [ -2.74864340e-01  -1.81113360e-01  -1.79334142e-01 ...,  -1.17064289e-01
   -1.36054075e-01  -3.51985787e-01]
 [  3.90208312e-02   8.39860085e-02  -4.07458871e-02 ...,   5.31935822e-02
    2.90612345e+00  -7.51972416e-02]]
Progress: 80.6% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.15954363]
 [-0.9501311 ]
 [-1.18897222]
 [-0.76346164]
 [-0.05821455]
 [ 2.64961771]
 [-0.05056266]
 [-1.09620629]
 [-0.52710696]
 [ 1.03156728]
 [-0.09038717]
 [ 0.14484311]
 [-0.09853984]
 [-1.0063453 ]
 [-0.30087425]
 [ 0.87355734]
 [-0.83375284]
 [-0.79197798]
 [-0.61833497]
 [ 0.1422367 ]
 [-0.34984905]
 [ 4.48546843]
 [-0.94578398]
 [-1.64525349]
 [ 0.38433088]
 [-0.3030403 ]
 [ 4.31923841]
 [-1.92243087]]
[[ -1.92670373e-02  -3.07463932e-01   2.65532512e-01 ...,  -2.32824507e-01
   -3.23900622e-01   2.83792866e-01]
 [  5.82672579e-02   1.44972965e-01  -2.15023607e-03 ...,  -2.22454829e-01
    1.62425675e+00   1.14323248e-01]
 [ -6.01814074e-02   2.63221837e-01   4.67306511e-01 ...,   2.37898600e-01
   -3.04964814e-01   9.57273841e-01]
 ..., 
 [ -1.84465824e-01  -2.39931752e-01  -3.87086416e-01 ...,   9.06589415e-02
   -5.92866928e-01  -3.28973566e-01]
 [ -2.74917694e-01  -1.81406896e-01  -1.79431101e-01 ...,  -1.17158513e-01
   -1.34774379e-01  -3.52213609e-01]
 [  3.90006241e-02   8.38964057e-02  -4.09584685e-02 ...,   5.31575643e-02
    2.90605757e+00  -7.54831764e-02]]
Progress: 80.7% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16611135]
 [-0.95679725]
 [-1.19402593]
 [-0.76991342]
 [-0.06503612]
 [ 2.64430846]
 [-0.0576102 ]
 [-1.10116409]
 [-0.53393999]
 [ 1.0281824 ]
 [-0.09627795]
 [ 0.13826394]
 [-0.10624051]
 [-1.01196966]
 [-0.30795289]
 [ 0.86553916]
 [-0.84037362]
 [-0.79617479]
 [-0.62410561]
 [ 0.13617975]
 [-0.35565657]
 [ 4.4841729 ]
 [-0.95087533]
 [-1.65015094]
 [ 0.37812526]
 [-0.30964263]
 [ 4.30844298]
 [-1.92581586]]
[[ -1.89386006e-02  -3.05537192e-01   2.67329952e-01 ...,  -2.32214559e-01
   -3.28979598e-01   2.86615507e-01]
 [  5.82811193e-02   1.45051482e-01  -2.03827142e-03 ...,  -2.22431475e-01
    1.62407188e+00   1.14445782e-01]
 [ -5.98754090e-02   2.64981720e-01   4.69614303e-01 ...,   2.38457792e-01
   -3.11438993e-01   9.60883043e-01]
 ..., 
 [ -1.84437125e-01  -2.39768969e-01  -3.87112992e-01 ...,   9.07146607e-02
   -5.94171357e-01  -3.28790509e-01]
 [ -2.74744274e-01  -1.80435001e-01  -1.78308485e-01 ...,  -1.16842439e-01
   -1.37867031e-01  -3.50600437e-01]
 [  3.90902659e-02   8.44307340e-02  -4.03460592e-02 ...,   5.33235505e-02
    2.90594446e+00  -7.48573692e-02]]
Progress: 80.7% ... Training loss: 0.065 ... Validation loss: 0.136[[-0.16021473]
 [-0.951847  ]
 [-1.19066872]
 [-0.7642152 ]
 [-0.0601698 ]
 [ 2.64638204]
 [-0.05280294]
 [-1.09692745]
 [-0.52909295]
 [ 1.03118739]
 [-0.09086624]
 [ 0.14312414]
 [-0.10075552]
 [-1.00903255]
 [-0.30245917]
 [ 0.87078013]
 [-0.83447533]
 [-0.79173769]
 [-0.62017205]
 [ 0.14125504]
 [-0.35098927]
 [ 4.4850156 ]
 [-0.94545883]
 [-1.64522122]
 [ 0.3818254 ]
 [-0.30467577]
 [ 4.31745047]
 [-1.92365231]]
[[ -1.90744250e-02  -3.06233441e-01   2.66902580e-01 ...,  -2.32449430e-01
   -3.27004351e-01   2.86152247e-01]
 [  5.83585826e-02   1.45497573e-01  -1.75750315e-03 ...,  -2.22294415e-01
    1.62396417e+00   1.15061495e-01]
 [ -5.99292461e-02   2.64620593e-01   4.68799347e-01 ...,   2.38345571e-01
   -3.10544648e-01   9.59015046e-01]
 ..., 
 [ -1.84506672e-01  -2.40158730e-01  -3.87567905e-01 ...,   9.06019714e-02
   -5.92914645e-01  -3.29101799e-01]
 [ -2.74818690e-01  -1.80861809e-01  -1.78652359e-01 ...,  -1.16981414e-01
   -1.37109918e-01  -3.51152094e-01]
 [  3.89695149e-02   8.37722117e-02  -4.09472936e-02 ...,   5.30966507e-02
    2.90599706e+00  -7.56124127e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16743552]
 [-0.95717117]
 [-1.19447955]
 [-0.77110587]
 [-0.06733029]
 [ 2.64483519]
 [-0.05891483]
 [-1.105     ]
 [-0.53419763]
 [ 1.0258324 ]
 [-0.09758614]
 [ 0.13631296]
 [-0.10724279]
 [-1.01188903]
 [-0.30896223]
 [ 0.86235279]
 [-0.84094037]
 [-0.79730551]
 [-0.62538294]
 [ 0.13510253]
 [-0.3580664 ]
 [ 4.48342554]
 [-0.95048978]
 [-1.65428835]
 [ 0.37679049]
 [-0.30928068]
 [ 4.30585726]
 [-1.92520964]]
[[ -1.89262304e-02  -3.05427839e-01   2.67726910e-01 ...,  -2.32190098e-01
   -3.28918451e-01   2.87036113e-01]
 [  5.83776803e-02   1.45600097e-01  -1.72466926e-03 ...,  -2.22264651e-01
    1.62389309e+00   1.15088732e-01]
 [ -6.02152426e-02   2.62982003e-01   4.67401278e-01 ...,   2.37836751e-01
   -3.09595099e-01   9.58287794e-01]
 ..., 
 [ -1.84471909e-01  -2.39995092e-01  -3.87250011e-01 ...,   9.06733012e-02
   -5.93586285e-01  -3.29214765e-01]
 [ -2.74640481e-01  -1.79835739e-01  -1.77554889e-01 ...,  -1.16679297e-01
   -1.38457018e-01  -3.50181871e-01]
 [  3.90092893e-02   8.39956538e-02  -4.08568867e-02 ...,   5.31690483e-02
    2.90585529e+00  -7.50299894e-02]]
Progress: 80.7% ... Training loss: 0.067 ... Validation loss: 0.136[[-0.16034966]
 [-0.95120743]
 [-1.18994628]
 [-0.76490749]
 [-0.06221533]
 [ 2.64901769]
 [-0.05262478]
 [-1.10031993]
 [-0.52819018]
 [ 1.03015115]
 [-0.09160474]
 [ 0.1419228 ]
 [-0.10088415]
 [-1.0066705 ]
 [-0.30329793]
 [ 0.86871442]
 [-0.83421317]
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 [-0.62078108]
 [ 0.14039085]
 [-0.35279602]
 [ 4.48455452]
 [-0.94420362]
 [-1.64898144]
 [ 0.38229731]
 [-0.3035922 ]
 [ 4.3164805 ]
 [-1.92155493]]
[[ -1.91192139e-02  -3.06481670e-01   2.66889682e-01 ...,  -2.32520238e-01
   -3.24854786e-01   2.85386918e-01]
 [  5.83749352e-02   1.45584951e-01  -1.73322690e-03 ...,  -2.22269657e-01
    1.62390552e+00   1.15070861e-01]
 [ -6.04296188e-02   2.61783240e-01   4.65431697e-01 ...,   2.37463666e-01
   -3.05112486e-01   9.55128292e-01]
 ..., 
 [ -1.84511147e-01  -2.40184066e-01  -3.87279449e-01 ...,   9.06013803e-02
   -5.92287619e-01  -3.29389865e-01]
 [ -2.74672715e-01  -1.80025722e-01  -1.77802414e-01 ...,  -1.16748241e-01
   -1.37022425e-01  -3.50781738e-01]
 [  3.89040322e-02   8.34033053e-02  -4.13997873e-02 ...,   5.29905603e-02
    2.90591945e+00  -7.62510390e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16400057]
 [-0.9545041 ]
 [-1.19270247]
 [-0.76849892]
 [-0.06511284]
 [ 2.64723417]
 [-0.056052  ]
 [-1.10294764]
 [-0.53185134]
 [ 1.02790124]
 [-0.09492341]
 [ 0.13898691]
 [-0.10373877]
 [-1.00934478]
 [-0.30636032]
 [ 0.86491743]
 [-0.83762872]
 [-0.79426531]
 [-0.62387393]
 [ 0.13769465]
 [-0.35533936]
 [ 4.48363815]
 [-0.9470788 ]
 [-1.65116149]
 [ 0.37950052]
 [-0.30728272]
 [ 4.31120032]
 [-1.92359194]]
[[ -1.90587575e-02  -3.06131101e-01   2.67374156e-01 ...,  -2.32390103e-01
   -3.27090575e-01   2.86220375e-01]
 [  5.83828920e-02   1.45632266e-01  -1.71481974e-03 ...,  -2.22254563e-01
    1.62386413e+00   1.15107573e-01]
 [ -6.02721244e-02   2.62758636e-01   4.66711117e-01 ...,   2.37770697e-01
   -3.07284091e-01   9.57106975e-01]
 ..., 
 [ -1.84404872e-01  -2.39570950e-01  -3.86576506e-01 ...,   9.07912249e-02
   -5.93122421e-01  -3.28615512e-01]
 [ -2.74610531e-01  -1.79665680e-01  -1.77618781e-01 ...,  -1.16627144e-01
   -1.38144673e-01  -3.50413692e-01]
 [  3.88534444e-02   8.31123583e-02  -4.17847647e-02 ...,   5.29066206e-02
    2.90608132e+00  -7.67184490e-02]]
Progress: 80.7% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.16186744]
 [-0.95163398]
 [-1.18984725]
 [-0.76724247]
 [-0.06306061]
 [ 2.64929373]
 [-0.05387147]
 [-1.10257099]
 [-0.52864333]
 [ 1.03003119]
 [-0.09317508]
 [ 0.14135687]
 [-0.10018385]
 [-1.00675217]
 [-0.30360164]
 [ 0.8677154 ]
 [-0.83512432]
 [-0.79188701]
 [-0.62094515]
 [ 0.14033102]
 [-0.35279681]
 [ 4.48549344]
 [-0.94544656]
 [-1.64975214]
 [ 0.38163408]
 [-0.30463662]
 [ 4.31506188]
 [-1.92195033]]
[[ -1.92769997e-02  -3.07347520e-01   2.66131133e-01 ...,  -2.32793147e-01
   -3.24532228e-01   2.84405942e-01]
 [  5.83892860e-02   1.45661525e-01  -1.66785369e-03 ...,  -2.22244534e-01
    1.62382577e+00   1.15139820e-01]
 [ -6.05043155e-02   2.61356884e-01   4.64974800e-01 ...,   2.37352877e-01
   -3.03149293e-01   9.54586369e-01]
 ..., 
 [ -1.84498655e-01  -2.40080197e-01  -3.87195901e-01 ...,   9.06362433e-02
   -5.92306472e-01  -3.29119628e-01]
 [ -2.74627137e-01  -1.79752996e-01  -1.77730647e-01 ...,  -1.16659708e-01
   -1.37560576e-01  -3.50500584e-01]
 [  3.88543367e-02   8.30878595e-02  -4.16459807e-02 ...,   5.29012617e-02
    2.90617470e+00  -7.64613092e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16288118]
 [-0.95234366]
 [-1.19017313]
 [-0.7678253 ]
 [-0.06376471]
 [ 2.64651574]
 [-0.05522826]
 [-1.1015593 ]
 [-0.53013173]
 [ 1.02980961]
 [-0.09325566]
 [ 0.14065095]
 [-0.10173397]
 [-1.00946586]
 [-0.30453455]
 [ 0.86583084]
 [-0.83568383]
 [-0.79243981]
 [-0.62138711]
 [ 0.13902808]
 [-0.35376152]
 [ 4.48511214]
 [-0.94691716]
 [-1.64770571]
 [ 0.37965575]
 [-0.30571737]
 [ 4.31459832]
 [-1.92294576]]
[[ -1.91706342e-02  -3.06775567e-01   2.66924190e-01 ...,  -2.32614220e-01
   -3.29347642e-01   2.85807493e-01]
 [  5.83062166e-02   1.45216730e-01  -2.24484545e-03 ...,  -2.22385809e-01
    1.62429121e+00   1.14509655e-01]
 [ -6.02230097e-02   2.62992540e-01   4.66462719e-01 ...,   2.37885985e-01
   -3.06639799e-01   9.56754600e-01]
 ..., 
 [ -1.84461804e-01  -2.39884936e-01  -3.87011728e-01 ...,   9.07082501e-02
   -5.93777037e-01  -3.28693323e-01]
 [ -2.74578692e-01  -1.79490503e-01  -1.77576843e-01 ...,  -1.16573574e-01
   -1.38435815e-01  -3.50234111e-01]
 [  3.87545610e-02   8.24908427e-02  -4.21540741e-02 ...,   5.27117781e-02
    2.90625995e+00  -7.71879252e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.16099527]
 [-0.95040007]
 [-1.18935071]
 [-0.76556584]
 [-0.06262875]
 [ 2.64893754]
 [-0.05328989]
 [-1.10079997]
 [-0.52925339]
 [ 1.02875922]
 [-0.09175764]
 [ 0.14195384]
 [-0.09973442]
 [-1.00795892]
 [-0.3032858 ]
 [ 0.8672429 ]
 [-0.83421604]
 [-0.79218069]
 [-0.62062066]
 [ 0.14032575]
 [-0.35304604]
 [ 4.48524932]
 [-0.94446968]
 [-1.64667911]
 [ 0.38137528]
 [-0.30401493]
 [ 4.31857698]
 [-1.92112792]]
[[ -1.92846142e-02  -3.07451812e-01   2.66503860e-01 ...,  -2.32828539e-01
   -3.29516701e-01   2.84457605e-01]
 [  5.83057592e-02   1.45201471e-01  -2.17447027e-03 ...,  -2.22389838e-01
    1.62426585e+00   1.14470687e-01]
 [ -6.03495459e-02   2.62231055e-01   4.65253571e-01 ...,   2.37660202e-01
   -3.06601181e-01   9.54819386e-01]
 ..., 
 [ -1.84496619e-01  -2.40080625e-01  -3.86963281e-01 ...,   9.06425906e-02
   -5.93559590e-01  -3.29036788e-01]
 [ -2.74535889e-01  -1.79296640e-01  -1.77447251e-01 ...,  -1.16513948e-01
   -1.39574065e-01  -3.49953366e-01]
 [  3.86111001e-02   8.16164048e-02  -4.29741992e-02 ...,   5.24482341e-02
    2.90678150e+00  -7.88062615e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15865233]
 [-0.94763503]
 [-1.18783502]
 [-0.76388765]
 [-0.06068279]
 [ 2.65200428]
 [-0.0507513 ]
 [-1.1002102 ]
 [-0.52647558]
 [ 1.03003572]
 [-0.09023282]
 [ 0.14391612]
 [-0.09721768]
 [-1.00519587]
 [-0.30085462]
 [ 0.86982411]
 [-0.83205893]
 [-0.79072591]
 [-0.61875465]
 [ 0.14307701]
 [-0.35099562]
 [ 4.48727712]
 [-0.9431169 ]
 [-1.64643037]
 [ 0.38362886]
 [-0.30119727]
 [ 4.32327059]
 [-1.91923527]]
[[ -1.94585812e-02  -3.08481129e-01   2.65587846e-01 ...,  -2.33155315e-01
   -3.27146154e-01   2.82504019e-01]
 [  5.83451425e-02   1.45438771e-01  -1.87822691e-03 ...,  -2.22314198e-01
    1.62413739e+00   1.14946258e-01]
 [ -6.06130484e-02   2.60705243e-01   4.64129687e-01 ...,   2.37152037e-01
   -3.03929182e-01   9.52290342e-01]
 ..., 
 [ -1.84515264e-01  -2.40238402e-01  -3.87043842e-01 ...,   9.05999525e-02
   -5.93606015e-01  -3.29496591e-01]
 [ -2.74570321e-01  -1.79498559e-01  -1.77688972e-01 ...,  -1.16587193e-01
   -1.39350627e-01  -3.50173968e-01]
 [  3.86123442e-02   8.16062361e-02  -4.32346116e-02 ...,   5.24524732e-02
    2.90696560e+00  -7.91604536e-02]]
Progress: 80.7% ... Training loss: 0.064 ... Validation loss: 0.140[[-0.1668897 ]
 [-0.9548236 ]
 [-1.19483169]
 [-0.77058381]
 [-0.06673495]
 [ 2.64760811]
 [-0.05746386]
 [-1.10490708]
 [-0.53453722]
 [ 1.02526038]
 [-0.09676665]
 [ 0.13685715]
 [-0.10500425]
 [-1.01147085]
 [-0.30829502]
 [ 0.86071858]
 [-0.84019793]
 [-0.79765502]
 [-0.62571974]
 [ 0.13586557]
 [-0.35854186]
 [ 4.48593626]
 [-0.94818926]
 [-1.65253361]
 [ 0.37721746]
 [-0.3078755 ]
 [ 4.31059511]
 [-1.92384083]]
[[ -1.91467035e-02  -3.06686606e-01   2.67805286e-01 ...,  -2.32580652e-01
   -3.31783131e-01   2.85779784e-01]
 [  5.83516105e-02   1.45459506e-01  -1.78573251e-03 ...,  -2.22306346e-01
    1.62409515e+00   1.14951588e-01]
 [ -6.03353363e-02   2.62367185e-01   4.66205009e-01 ...,   2.37698233e-01
   -3.08465806e-01   9.55882949e-01]
 ..., 
 [ -1.84486569e-01  -2.40061267e-01  -3.86817608e-01 ...,   9.06573152e-02
   -5.94073600e-01  -3.29021552e-01]
 [ -2.74526647e-01  -1.79249199e-01  -1.77466325e-01 ...,  -1.16511604e-01
   -1.40295156e-01  -3.50066529e-01]
 [  3.87123916e-02   8.21970732e-02  -4.26496526e-02 ...,   5.26477909e-02
    2.90693830e+00  -7.82397617e-02]]
Progress: 80.7% ... Training loss: 0.065 ... Validation loss: 0.136[[-0.15496302]
 [-0.94504503]
 [-1.18649511]
 [-0.76082933]
 [-0.05693753]
 [ 2.65243556]
 [-0.04750041]
 [-1.09566443]
 [-0.52483731]
 [ 1.03339356]
 [-0.08642447]
 [ 0.14713081]
 [-0.0942611 ]
 [-1.00444464]
 [-0.29758858]
 [ 0.87317465]
 [-0.82900828]
 [-0.78749   ]
 [-0.61686768]
 [ 0.14605483]
 [-0.34844024]
 [ 4.48803122]
 [-0.9391664 ]
 [-1.64134985]
 [ 0.38577778]
 [-0.29898588]
 [ 4.32811518]
 [-1.91980593]]
[[ -1.95460400e-02  -3.08855433e-01   2.65872393e-01 ...,  -2.33289386e-01
   -3.25913608e-01   2.83101064e-01]
 [  5.83456238e-02   1.45426050e-01  -1.82016553e-03 ...,  -2.22317306e-01
    1.62416804e+00   1.14851978e-01]
 [ -6.03874794e-02   2.62087144e-01   4.65562975e-01 ...,   2.37590725e-01
   -3.05561873e-01   9.53389154e-01]
 ..., 
 [ -1.84489976e-01  -2.40053943e-01  -3.86770222e-01 ...,   9.06491829e-02
   -5.93505124e-01  -3.29152332e-01]
 [ -2.74626134e-01  -1.79780377e-01  -1.78119185e-01 ...,  -1.16683104e-01
   -1.38546825e-01  -3.50753992e-01]
 [  3.86703599e-02   8.19541817e-02  -4.29417588e-02 ...,   5.25754425e-02
    2.90692178e+00  -7.85723969e-02]]
Progress: 80.7% ... Training loss: 0.069 ... Validation loss: 0.149[[-0.16467773]
 [-0.95296732]
 [-1.19405907]
 [-0.76875191]
 [-0.06463268]
 [ 2.64861072]
 [-0.05553253]
 [-1.10212036]
 [-0.53400492]
 [ 1.0264059 ]
 [-0.09490507]
 [ 0.1387366 ]
 [-0.10342545]
 [-1.01116668]
 [-0.30651244]
 [ 0.86377433]
 [-0.8387322 ]
 [-0.79591351]
 [-0.62517224]
 [ 0.13820554]
 [-0.3572087 ]
 [ 4.48664158]
 [-0.94680678]
 [-1.64938076]
 [ 0.37899086]
 [-0.3070068 ]
 [ 4.31362747]
 [-1.92415283]]
[[ -1.92629561e-02  -3.07316261e-01   2.67621160e-01 ...,  -2.32781091e-01
   -3.30708779e-01   2.85615018e-01]
 [  5.83824440e-02   1.45630025e-01  -1.59260695e-03 ...,  -2.22252677e-01
    1.62400998e+00   1.15084075e-01]
 [ -6.01751461e-02   2.63408483e-01   4.67388336e-01 ...,   2.38011775e-01
   -3.11415238e-01   9.57020619e-01]
 ..., 
 [ -1.84323315e-01  -2.39060549e-01  -3.85720813e-01 ...,   9.09656473e-02
   -5.96668756e-01  -3.27616911e-01]
 [ -2.74613617e-01  -1.79715765e-01  -1.78159999e-01 ...,  -1.16644661e-01
   -1.39075477e-01  -3.50922074e-01]
 [  3.87981303e-02   8.27153916e-02  -4.20535004e-02 ...,   5.28096913e-02
    2.90680265e+00  -7.71685943e-02]]
Progress: 80.7% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15987995]
 [-0.94887356]
 [-1.19022202]
 [-0.7653667 ]
 [-0.06128885]
 [ 2.65201226]
 [-0.05185003]
 [-1.09908763]
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 [ 1.02879236]
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 [ 0.14311477]
 [-0.09896366]
 [-1.00835171]
 [-0.30202413]
 [ 0.8686043 ]
 [-0.83412644]
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 [ 0.14228109]
 [-0.35290499]
 [ 4.48757391]
 [-0.94402386]
 [-1.64470267]
 [ 0.38260443]
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 [ 4.32164586]
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[[ -1.95858632e-02  -3.09060976e-01   2.66087209e-01 ...,  -2.33352235e-01
   -3.26651588e-01   2.82977043e-01]
 [  5.83304631e-02   1.45341141e-01  -1.81816804e-03 ...,  -2.22354782e-01
    1.62534863e+00   1.14664484e-01]
 [ -6.03084241e-02   2.62609785e-01   4.66258133e-01 ...,   2.37749011e-01
   -3.10625649e-01   9.54928423e-01]
 ..., 
 [ -1.84397597e-01  -2.39439944e-01  -3.86200560e-01 ...,   9.08371673e-02
   -5.95424791e-01  -3.27999006e-01]
 [ -2.74603893e-01  -1.79654785e-01  -1.78027202e-01 ...,  -1.16634780e-01
   -1.39628481e-01  -3.50868418e-01]
 [  3.87400046e-02   8.23591647e-02  -4.22889178e-02 ...,   5.26880038e-02
    2.90673517e+00  -7.79911363e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16335707]
 [-0.95158404]
 [-1.19338589]
 [-0.76805853]
 [-0.06387726]
 [ 2.64944238]
 [-0.05448809]
 [-1.10127307]
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 [ 1.02687077]
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 [ 0.13985334]
 [-0.10218318]
 [-1.01031012]
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 [ 0.86485099]
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 [ 0.13942543]
 [-0.35630864]
 [ 4.4864761 ]
 [-0.94570925]
 [-1.64780379]
 [ 0.38017079]
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 [ 4.31605555]
 [-1.92280598]]
[[ -1.93477140e-02  -3.07669813e-01   2.67527353e-01 ...,  -2.32896957e-01
   -3.29759026e-01   2.84619222e-01]
 [  5.83555568e-02   1.45486965e-01  -1.73263229e-03 ...,  -2.22308225e-01
    1.62532986e+00   1.14845131e-01]
 [ -6.02121033e-02   2.63271898e-01   4.67184276e-01 ...,   2.37951480e-01
   -3.12014941e-01   9.55972902e-01]
 ..., 
 [ -1.84366464e-01  -2.39293670e-01  -3.86127404e-01 ...,   9.08915207e-02
   -5.95712009e-01  -3.27933530e-01]
 [ -2.74675655e-01  -1.80078607e-01  -1.78467012e-01 ...,  -1.16759050e-01
   -1.40027323e-01  -3.51604650e-01]
 [  3.86499264e-02   8.18212899e-02  -4.27829290e-02 ...,   5.25199545e-02
    2.90695229e+00  -7.85166635e-02]]
Progress: 80.7% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.15904788]
 [-0.94846099]
 [-1.18922028]
 [-0.76464431]
 [-0.05963228]
 [ 2.64903757]
 [-0.05137851]
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 [ 1.03017222]
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 [ 0.14366734]
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 [-1.00877035]
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 [ 0.86935881]
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 [ 4.48641158]
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 [ 0.38280402]
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 [ 4.32304883]
 [-1.92195028]]
[[ -1.94572204e-02  -3.08255325e-01   2.66788836e-01 ...,  -2.33097933e-01
   -3.28809898e-01   2.84251183e-01]
 [  5.81753595e-02   1.44465595e-01  -2.64705908e-03 ...,  -2.22629732e-01
    1.62637412e+00   1.13583044e-01]
 [ -6.01280999e-02   2.63653570e-01   4.67080108e-01 ...,   2.38096536e-01
   -3.12420488e-01   9.56070558e-01]
 ..., 
 [ -1.84369559e-01  -2.39305405e-01  -3.86110907e-01 ...,   9.08841227e-02
   -5.95841324e-01  -3.27879309e-01]
 [ -2.74766327e-01  -1.80591365e-01  -1.78836041e-01 ...,  -1.16923571e-01
   -1.39341296e-01  -3.52224688e-01]
 [  3.86265772e-02   8.16788500e-02  -4.30216775e-02 ...,   5.24719286e-02
    2.90707733e+00  -7.89399174e-02]]
Progress: 80.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16263129]
 [-0.95162401]
 [-1.19207278]
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 [-0.06295695]
 [ 2.65056089]
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 [ 4.48680427]
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 [ 0.38172851]
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 [ 4.31692867]
 [-1.92246479]]
[[ -1.95540893e-02  -3.08771564e-01   2.66348695e-01 ...,  -2.33275405e-01
   -3.25662286e-01   2.83202300e-01]
 [  5.81846130e-02   1.44506604e-01  -2.61706417e-03 ...,  -2.22617187e-01
    1.62658422e+00   1.13535327e-01]
 [ -6.04169143e-02   2.61962934e-01   4.66088258e-01 ...,   2.37531157e-01
   -3.10594114e-01   9.55598943e-01]
 ..., 
 [ -1.84318451e-01  -2.39037149e-01  -3.85590715e-01 ...,   9.09695330e-02
   -5.96721644e-01  -3.27537334e-01]
 [ -2.74795828e-01  -1.80715764e-01  -1.78864838e-01 ...,  -1.16973570e-01
   -1.38316139e-01  -3.52432874e-01]
 [  3.85954718e-02   8.15004948e-02  -4.32521884e-02 ...,   5.24104103e-02
    2.90734588e+00  -7.94992433e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16121104]
 [-0.95050085]
 [-1.19171448]
 [-0.76715738]
 [-0.06129417]
 [ 2.65139462]
 [-0.05238392]
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 [ 1.02729566]
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 [ 0.14283919]
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 [ 0.86876177]
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 [ 0.14138563]
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 [ 4.48619958]
 [-0.94549062]
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 [ 0.38352265]
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 [ 4.31985805]
 [-1.92258877]]
[[ -1.95373152e-02  -3.08643629e-01   2.66576012e-01 ...,  -2.33230785e-01
   -3.26903514e-01   2.83523054e-01]
 [  5.81584735e-02   1.44365263e-01  -2.81471423e-03 ...,  -2.22661185e-01
    1.62695727e+00   1.13379078e-01]
 [ -6.03506164e-02   2.62272931e-01   4.66830393e-01 ...,   2.37665415e-01
   -3.12440174e-01   9.56258124e-01]
 ..., 
 [ -1.84290550e-01  -2.38870510e-01  -3.85409223e-01 ...,   9.10222157e-02
   -5.97165940e-01  -3.27516126e-01]
 [ -2.74823758e-01  -1.80903395e-01  -1.78959181e-01 ...,  -1.17033421e-01
   -1.37093160e-01  -3.52400534e-01]
 [  3.85838603e-02   8.14267948e-02  -4.32733879e-02 ...,   5.23804864e-02
    2.90744949e+00  -7.96188415e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16365806]
 [-0.95325157]
 [-1.1940944 ]
 [-0.76936318]
 [-0.06242246]
 [ 2.64865283]
 [-0.05486772]
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 [ 1.02633799]
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 [ 0.14089203]
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 [ 4.48574522]
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 [ 0.38143015]
 [-0.30731234]
 [ 4.31542571]
 [-1.92510828]]
[[ -1.93653993e-02  -3.07607655e-01   2.67629271e-01 ...,  -2.32892702e-01
   -3.28993238e-01   2.85140131e-01]
 [  5.81736372e-02   1.44454435e-01  -2.74317356e-03 ...,  -2.22639908e-01
    1.62688543e+00   1.13521697e-01]
 [ -6.00678080e-02   2.63878959e-01   4.68883949e-01 ...,   2.38186259e-01
   -3.14795594e-01   9.58776741e-01]
 ..., 
 [ -1.84172654e-01  -2.38205860e-01  -3.84837286e-01 ...,   9.12414510e-02
   -5.98983995e-01  -3.26948498e-01]
 [ -2.74897382e-01  -1.81307071e-01  -1.79401432e-01 ...,  -1.17154624e-01
   -1.36213892e-01  -3.52818313e-01]
 [  3.86688906e-02   8.19025387e-02  -4.26706365e-02 ...,   5.25432559e-02
    2.90727279e+00  -7.89564297e-02]]
Progress: 80.8% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.15984234]
 [-0.95069144]
 [-1.19086991]
 [-0.76706096]
 [-0.06014005]
 [ 2.65152809]
 [-0.05141291]
 [-1.09979842]
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 [ 1.02841909]
 [-0.09195763]
 [ 0.14419725]
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 [-0.35060145]
 [ 4.4864374 ]
 [-0.94622869]
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 [ 0.38467465]
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 [ 4.32172141]
 [-1.92292045]]
[[-0.01965337 -0.30921289  0.26606265 ..., -0.23339204 -0.32610417
   0.28256313]
 [ 0.05813738  0.14424008 -0.00301406 ..., -0.22270912  1.62786808
   0.11300175]
 [-0.06022366  0.26300434  0.46785334 ...,  0.23789865 -0.31148243
   0.95707152]
 ..., 
 [-0.1842039  -0.23838436 -0.38532199 ...,  0.09118502 -0.59900252
  -0.32731396]
 [-0.27507831 -0.18234793 -0.18051836 ..., -0.11746698 -0.13384794
  -0.3544959 ]
 [ 0.03859161  0.08147569 -0.04299738 ...,  0.05240076  2.90760762
  -0.07958344]]
Progress: 80.8% ... Training loss: 0.062 ... Validation loss: 0.139[[-0.16032782]
 [-0.95121291]
 [-1.1927008 ]
 [-0.76711112]
 [-0.06065761]
 [ 2.65189083]
 [-0.05145173]
 [-1.09907692]
 [-0.53021134]
 [ 1.02793095]
 [-0.09225486]
 [ 0.1437553 ]
 [-0.09861479]
 [-1.00878787]
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 [ 0.86950684]
 [-0.83583242]
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 [-0.62174923]
 [ 0.1421998 ]
 [-0.35124853]
 [ 4.48671971]
 [-0.94559836]
 [-1.64374342]
 [ 0.38459356]
 [-0.30525014]
 [ 4.32123319]
 [-1.92342728]]
[[-0.0195696  -0.30873621  0.26651995 ..., -0.23323922 -0.3278606
   0.28335079]
 [ 0.05810396  0.14404372 -0.00318664 ..., -0.22277038  1.62793264
   0.11289434]
 [-0.06010498  0.26365776  0.46846407 ...,  0.23811403 -0.31177973
   0.95749838]
 ..., 
 [-0.18422673 -0.2385124  -0.38551997 ...,  0.09114524 -0.59884547
  -0.32753514]
 [-0.27513464 -0.18272239 -0.18074302 ..., -0.11757258 -0.13244619
  -0.35510362]
 [ 0.03858964  0.08146636 -0.04293273 ...,  0.05239655  2.90759344
  -0.07947923]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16014084]
 [-0.95008557]
 [-1.19176915]
 [-0.76623047]
 [-0.05955863]
 [ 2.65232588]
 [-0.05163086]
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 [-0.52958342]
 [ 1.02760944]
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 [ 0.14389296]
 [-0.09820616]
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 [-0.35154953]
 [ 4.4869209 ]
 [-0.94558692]
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 [ 0.38463966]
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 [ 4.32169353]
 [-1.92291588]]
[[ -1.95449363e-02  -3.08602543e-01   2.66763139e-01 ...,  -2.33213648e-01
   -3.28592112e-01   2.83445663e-01]
 [  5.81978393e-02   1.44591782e-01  -2.58839351e-03 ...,  -2.22596169e-01
    1.62768705e+00   1.13456620e-01]
 [ -6.02066322e-02   2.63061192e-01   4.67941915e-01 ...,   2.37947340e-01
   -3.10706291e-01   9.56071214e-01]
 ..., 
 [ -1.84216068e-01  -2.38474243e-01  -3.85417606e-01 ...,   9.11789092e-02
   -5.98415603e-01  -3.27845264e-01]
 [ -2.75168726e-01  -1.82918231e-01  -1.81017960e-01 ...,  -1.17648587e-01
   -1.32896283e-01  -3.55191133e-01]
 [  3.85336743e-02   8.11431842e-02  -4.32756763e-02 ...,   5.22768081e-02
    2.90760974e+00  -7.96597547e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16214841]
 [-0.95140117]
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 [ 2.65173915]
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 [ 4.3180461 ]
 [-1.92240249]]
[[ -1.94318065e-02  -3.07970779e-01   2.67143158e-01 ...,  -2.33018423e-01
   -3.29077262e-01   2.83980762e-01]
 [  5.82145449e-02   1.44690596e-01  -2.66390841e-03 ...,  -2.22563203e-01
    1.62734304e+00   1.13382418e-01]
 [ -6.05337866e-02   2.61228986e-01   4.66069895e-01 ...,   2.37359223e-01
   -3.08281188e-01   9.53516113e-01]
 ..., 
 [ -1.84184018e-01  -2.38297011e-01  -3.85586416e-01 ...,   9.12360958e-02
   -5.98575593e-01  -3.27511796e-01]
 [ -2.75111694e-01  -1.82593278e-01  -1.80808324e-01 ...,  -1.17550222e-01
   -1.33453385e-01  -3.54902085e-01]
 [  3.87137020e-02   8.21893732e-02  -4.24414196e-02 ...,   5.25999060e-02
    2.90733021e+00  -7.89525447e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.1603918 ]
 [-0.95046672]
 [-1.1910107 ]
 [-0.76719542]
 [-0.06059095]
 [ 2.65160262]
 [-0.05214797]
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 [ 1.02878506]
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 [ 0.14271228]
 [-0.09942365]
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 [ 4.48723801]
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 [ 0.38458115]
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 [ 4.32058135]
 [-1.92256656]]
[[ -1.94327177e-02  -3.07948174e-01   2.67184952e-01 ...,  -2.33035490e-01
   -3.29575331e-01   2.84421635e-01]
 [  5.81961738e-02   1.44585649e-01  -2.80988483e-03 ...,  -2.22597069e-01
    1.62776094e+00   1.13154610e-01]
 [ -6.03910236e-02   2.62030347e-01   4.66476998e-01 ...,   2.37603561e-01
   -3.10644070e-01   9.54753241e-01]
 ..., 
 [ -1.84197664e-01  -2.38376994e-01  -3.85740882e-01 ...,   9.12096585e-02
   -5.98425328e-01  -3.27622962e-01]
 [ -2.75080876e-01  -1.82400435e-01  -1.80452876e-01 ...,  -1.17492875e-01
   -1.33699844e-01  -3.54438937e-01]
 [  3.87153605e-02   8.21713969e-02  -4.22775055e-02 ...,   5.26019603e-02
    2.90727353e+00  -7.88123156e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16605913]
 [-0.95522449]
 [-1.1949935 ]
 [-0.77140206]
 [-0.06424051]
 [ 2.64751788]
 [-0.05713338]
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 [ 1.02598291]
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 [ 0.13758686]
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 [-1.01256821]
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 [ 0.86212698]
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 [ 0.13723946]
 [-0.3570882 ]
 [ 4.48712036]
 [-0.95055583]
 [-1.64990499]
 [ 0.37962195]
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 [ 4.3121211 ]
 [-1.92540834]]
[[ -1.91200668e-02  -3.06161517e-01   2.69273855e-01 ...,  -2.32464141e-01
   -3.33276631e-01   2.86964879e-01]
 [  5.82007066e-02   1.44612743e-01  -2.73833623e-03 ...,  -2.22590838e-01
    1.62772639e+00   1.13257545e-01]
 [ -6.02398305e-02   2.62882751e-01   4.67766631e-01 ...,   2.37902025e-01
   -3.13962560e-01   9.56546290e-01]
 ..., 
 [ -1.84067137e-01  -2.37695284e-01  -3.85089566e-01 ...,   9.14556386e-02
   -6.00638454e-01  -3.26735427e-01]
 [ -2.75048673e-01  -1.82225771e-01  -1.80171658e-01 ...,  -1.17435720e-01
   -1.34318715e-01  -3.54156498e-01]
 [  3.87895669e-02   8.26147947e-02  -4.18510658e-02 ...,   5.27354749e-02
    2.90710437e+00  -7.79553118e-02]]
Progress: 80.8% ... Training loss: 0.065 ... Validation loss: 0.135[[-0.16089071]
 [-0.9499111 ]
 [-1.1903146 ]
 [-0.76660806]
 [-0.0589342 ]
 [ 2.64813123]
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 [ 1.03181091]
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 [-1.01013565]
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 [ 0.86828304]
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 [-0.79240699]
 [-0.61970414]
 [ 0.14212881]
 [-0.35174497]
 [ 4.48865288]
 [-0.94696979]
 [-1.64406609]
 [ 0.38302462]
 [-0.30458705]
 [ 4.31996024]
 [-1.92407015]]
[[ -1.90785173e-02  -3.05949441e-01   2.69632181e-01 ...,  -2.32418358e-01
   -3.30110792e-01   2.86930033e-01]
 [  5.82660985e-02   1.44978035e-01  -2.30748987e-03 ...,  -2.22493503e-01
    1.62756771e+00   1.13943299e-01]
 [ -6.02272187e-02   2.63009892e-01   4.67914292e-01 ...,   2.37917140e-01
   -3.11433279e-01   9.55950955e-01]
 ..., 
 [ -1.84171771e-01  -2.38306813e-01  -3.85639866e-01 ...,   9.12673362e-02
   -5.98828394e-01  -3.27752608e-01]
 [ -2.75199261e-01  -1.83075919e-01  -1.81199202e-01 ...,  -1.17714662e-01
   -1.32746347e-01  -3.55234003e-01]
 [  3.88087637e-02   8.27085004e-02  -4.19235157e-02 ...,   5.27614333e-02
    2.90700315e+00  -7.74996841e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16011067]
 [-0.94978392]
 [-1.1908967 ]
 [-0.7662487 ]
 [-0.05889052]
 [ 2.64857926]
 [-0.05222762]
 [-1.10036307]
 [-0.52784498]
 [ 1.03085684]
 [-0.09271863]
 [ 0.14266957]
 [-0.09967556]
 [-1.01007671]
 [-0.30161459]
 [ 0.86849076]
 [-0.83567116]
 [-0.7924019 ]
 [-0.61963169]
 [ 0.14287543]
 [-0.35123612]
 [ 4.48952605]
 [-0.94592405]
 [-1.6436    ]
 [ 0.38349044]
 [-0.30470727]
 [ 4.32098456]
 [-1.92422358]]
[[ -1.92488349e-02  -3.06939435e-01   2.68916562e-01 ...,  -2.32722653e-01
   -3.29195021e-01   2.85389633e-01]
 [  5.82621214e-02   1.44954977e-01  -2.33526993e-03 ...,  -2.22500979e-01
    1.62761675e+00   1.13913810e-01]
 [ -6.01811495e-02   2.63187653e-01   4.68379946e-01 ...,   2.38033018e-01
   -3.11024411e-01   9.56327899e-01]
 ..., 
 [ -1.84176132e-01  -2.38337913e-01  -3.85583404e-01 ...,   9.12595702e-02
   -5.98877590e-01  -3.27738117e-01]
 [ -2.75165930e-01  -1.82885565e-01  -1.81117537e-01 ...,  -1.17645647e-01
   -1.34160688e-01  -3.55338572e-01]
 [  3.87819368e-02   8.25194982e-02  -4.18039768e-02 ...,   5.27253969e-02
    2.90707550e+00  -7.76144190e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.1609791 ]
 [-0.95002886]
 [-1.19148472]
 [-0.7668991 ]
 [-0.05939698]
 [ 2.65069872]
 [-0.05218324]
 [-1.10268587]
 [-0.52757023]
 [ 1.03055746]
 [-0.09349647]
 [ 0.14178435]
 [-0.09981811]
 [-1.00860395]
 [-0.3023277 ]
 [ 0.86738664]
 [-0.83668374]
 [-0.79376447]
 [-0.6204364 ]
 [ 0.14259946]
 [-0.35219313]
 [ 4.48987479]
 [-0.9459193 ]
 [-1.64696207]
 [ 0.38376984]
 [-0.30431455]
 [ 4.31951746]
 [-1.92362475]]
[[ -1.92993155e-02  -3.07242760e-01   2.68923539e-01 ...,  -2.32835767e-01
   -3.28997426e-01   2.84876433e-01]
 [  5.82275434e-02   1.44777394e-01  -2.31819213e-03 ...,  -2.22565957e-01
    1.62788494e+00   1.13807009e-01]
 [ -6.04800306e-02   2.61407158e-01   4.66778087e-01 ...,   2.37483185e-01
   -3.06844020e-01   9.54369343e-01]
 ..., 
 [ -1.84173359e-01  -2.38375346e-01  -3.85611177e-01 ...,   9.12628574e-02
   -5.98523364e-01  -3.27832160e-01]
 [ -2.75107482e-01  -1.82574856e-01  -1.80830365e-01 ...,  -1.17550868e-01
   -1.34439591e-01  -3.55070291e-01]
 [  3.88808218e-02   8.30739212e-02  -4.12434900e-02 ...,   5.28995844e-02
    2.90702614e+00  -7.71003728e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16484214]
 [-0.95310871]
 [-1.19309691]
 [-0.76977939]
 [-0.06129974]
 [ 2.64828293]
 [-0.05528277]
 [-1.1044632 ]
 [-0.52981081]
 [ 1.02958674]
 [-0.09644935]
 [ 0.13975012]
 [-0.10281161]
 [-1.01069688]
 [-0.30534863]
 [ 0.8652398 ]
 [-0.84027263]
 [-0.79661134]
 [-0.62225454]
 [ 0.14019838]
 [-0.35441905]
 [ 4.48885171]
 [-0.94978828]
 [-1.64988748]
 [ 0.38163651]
 [-0.30699334]
 [ 4.31320433]
 [-1.92585903]]
[[ -1.92242571e-02  -3.06751043e-01   2.69421633e-01 ...,  -2.32678251e-01
   -3.27675347e-01   2.85100104e-01]
 [  5.82054845e-02   1.44668227e-01  -2.54259319e-03 ...,  -2.22601301e-01
    1.62836196e+00   1.13656311e-01]
 [ -6.03603912e-02   2.61971284e-01   4.67959304e-01 ...,   2.37716697e-01
   -3.06388878e-01   9.56951189e-01]
 ..., 
 [ -1.84207383e-01  -2.38566558e-01  -3.85870191e-01 ...,   9.12022861e-02
   -5.97571508e-01  -3.28216552e-01]
 [ -2.75203840e-01  -1.83147771e-01  -1.81529836e-01 ...,  -1.17731634e-01
   -1.33218518e-01  -3.55608469e-01]
 [  3.90498620e-02   8.39907475e-02  -4.01377443e-02 ...,   5.32170862e-02
    2.90692167e+00  -7.53791862e-02]]
Progress: 80.8% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.1596698 ]
 [-0.94815911]
 [-1.18895194]
 [-0.76520783]
 [-0.05654486]
 [ 2.65186009]
 [-0.0497342 ]
 [-1.10039022]
 [-0.52574778]
 [ 1.03261818]
 [-0.09157932]
 [ 0.14508595]
 [-0.09600455]
 [-1.00668936]
 [-0.29971767]
 [ 0.87140675]
 [-0.83489057]
 [-0.79200674]
 [-0.61794112]
 [ 0.14488754]
 [-0.34901147]
 [ 4.49019654]
 [-0.9453187 ]
 [-1.64506098]
 [ 0.38638874]
 [-0.30226054]
 [ 4.32264198]
 [-1.92375138]]
[[ -1.95318121e-02  -3.08415778e-01   2.67638410e-01 ...,  -2.33214774e-01
   -3.23391252e-01   2.82730214e-01]
 [  5.81798430e-02   1.44524061e-01  -2.71878873e-03 ...,  -2.22647318e-01
    1.62882578e+00   1.13381117e-01]
 [ -6.04331325e-02   2.61434115e-01   4.66965430e-01 ...,   2.37558903e-01
   -3.04665760e-01   9.55475102e-01]
 ..., 
 [ -1.84196085e-01  -2.38491397e-01  -3.85730972e-01 ...,   9.12224061e-02
   -5.97442393e-01  -3.27971078e-01]
 [ -2.75319801e-01  -1.83794905e-01  -1.82269669e-01 ...,  -1.17920268e-01
   -1.31584147e-01  -3.56713591e-01]
 [  3.89107811e-02   8.31940321e-02  -4.07690162e-02 ...,   5.29576889e-02
    2.90705721e+00  -7.65884578e-02]]
Progress: 80.8% ... Training loss: 0.064 ... Validation loss: 0.142[[-0.16130524]
 [-0.94980064]
 [-1.19010569]
 [-0.76768004]
 [-0.05862586]
 [ 2.65356362]
 [-0.05119198]
 [-1.10282905]
 [-0.52703011]
 [ 1.0299502 ]
 [-0.09340361]
 [ 0.14352892]
 [-0.09744044]
 [-1.00751378]
 [-0.3009245 ]
 [ 0.86993598]
 [-0.83686626]
 [-0.79416148]
 [-0.61879672]
 [ 0.1432627 ]
 [-0.35063822]
 [ 4.4898272 ]
 [-0.94734339]
 [-1.64766107]
 [ 0.38606029]
 [-0.30391346]
 [ 4.32004622]
 [-1.92396396]]
[[ -1.96699752e-02  -3.09239035e-01   2.66757245e-01 ...,  -2.33475102e-01
   -3.22875629e-01   2.81119732e-01]
 [  5.81639945e-02   1.44430041e-01  -2.86980050e-03 ...,  -2.22674420e-01
    1.62930421e+00   1.13097871e-01]
 [ -6.05964324e-02   2.60491663e-01   4.66240516e-01 ...,   2.37263249e-01
   -3.04716414e-01   9.54722791e-01]
 ..., 
 [ -1.84182551e-01  -2.38414778e-01  -3.85629205e-01 ...,   9.12489097e-02
   -5.96967077e-01  -3.27721262e-01]
 [ -2.75271180e-01  -1.83529380e-01  -1.81921946e-01 ...,  -1.17830934e-01
   -1.32295400e-01  -3.56353456e-01]
 [  3.88293847e-02   8.27100443e-02  -4.12117143e-02 ...,   5.27989877e-02
    2.90722931e+00  -7.77259495e-02]]
Progress: 80.9% ... Training loss: 0.062 ... Validation loss: 0.138[[-0.16567029]
 [-0.95364006]
 [-1.19335424]
 [-0.77138344]
 [-0.06199931]
 [ 2.65130148]
 [-0.05505455]
 [-1.10538734]
 [-0.53100254]
 [ 1.02757247]
 [-0.09708706]
 [ 0.13986306]
 [-0.10211299]
 [-1.01046501]
 [-0.30533834]
 [ 0.8656335 ]
 [-0.84111275]
 [-0.79772711]
 [-0.62182789]
 [ 0.13937445]
 [-0.35462085]
 [ 4.48972242]
 [-0.95098893]
 [-1.65120459]
 [ 0.38296276]
 [-0.30780878]
 [ 4.31304065]
 [-1.9260487 ]]
[[ -1.94880796e-02  -3.08218459e-01   2.67564019e-01 ...,  -2.33133552e-01
   -3.24508833e-01   2.82413246e-01]
 [  5.82304804e-02   1.44815106e-01  -2.68502178e-03 ...,  -2.22552556e-01
    1.62924135e+00   1.13539730e-01]
 [ -6.04679398e-02   2.61229372e-01   4.67450859e-01 ...,   2.37496538e-01
   -3.08293878e-01   9.56311023e-01]
 ..., 
 [ -1.84134531e-01  -2.38133079e-01  -3.85345747e-01 ...,   9.13378346e-02
   -5.96367150e-01  -3.27342670e-01]
 [ -2.75152573e-01  -1.82883621e-01  -1.81491948e-01 ...,  -1.17621067e-01
   -1.34007501e-01  -3.55593834e-01]
 [  3.89170668e-02   8.32572766e-02  -4.06934149e-02 ...,   5.29743738e-02
    2.90709733e+00  -7.72937422e-02]]
Progress: 80.9% ... Training loss: 0.062 ... Validation loss: 0.134[[-0.16379397]
 [-0.9520276 ]
 [-1.191849  ]
 [-0.76912577]
 [-0.05966605]
 [ 2.65139329]
 [-0.05339634]
 [-1.10275782]
 [-0.52947585]
 [ 1.02939767]
 [-0.09506609]
 [ 0.14148392]
 [-0.10003332]
 [-1.00891531]
 [-0.30366902]
 [ 0.8675368 ]
 [-0.83913868]
 [-0.79589919]
 [-0.62038151]
 [ 0.14118504]
 [-0.35257441]
 [ 4.489481  ]
 [-0.94874382]
 [-1.64860778]
 [ 0.38421274]
 [-0.30632524]
 [ 4.31601311]
 [-1.92555978]]
[[ -1.94823594e-02  -3.08240759e-01   2.67621984e-01 ...,  -2.33104343e-01
   -3.24556209e-01   2.82438989e-01]
 [  5.81902805e-02   1.44587999e-01  -2.77275288e-03 ...,  -2.22625051e-01
    1.62937243e+00   1.13325361e-01]
 [ -6.03675866e-02   2.61806260e-01   4.67663271e-01 ...,   2.37672677e-01
   -3.07704859e-01   9.56361299e-01]
 ..., 
 [ -1.84138019e-01  -2.38157869e-01  -3.85401934e-01 ...,   9.13335395e-02
   -5.96030367e-01  -3.27518173e-01]
 [ -2.75175046e-01  -1.83076856e-01  -1.81595760e-01 ...,  -1.17654115e-01
   -1.34514755e-01  -3.55804256e-01]
 [  3.89287801e-02   8.33128663e-02  -4.05243732e-02 ...,   5.29952253e-02
    2.90706550e+00  -7.70019513e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.16603443]
 [-0.95396909]
 [-1.19350553]
 [-0.77114665]
 [-0.06145591]
 [ 2.65075822]
 [-0.05516464]
 [-1.10461213]
 [-0.53122367]
 [ 1.02904225]
 [-0.09675919]
 [ 0.13937736]
 [-0.10215591]
 [-1.00974978]
 [-0.30573846]
 [ 0.86483781]
 [-0.8411232 ]
 [-0.79783292]
 [-0.6221614 ]
 [ 0.1390986 ]
 [-0.35458819]
 [ 4.49023283]
 [-0.95040042]
 [-1.65107679]
 [ 0.38217044]
 [-0.30779436]
 [ 4.31235405]
 [-1.9268147 ]]
[[ -1.93959416e-02  -3.07731823e-01   2.67833881e-01 ...,  -2.32936891e-01
   -3.24524792e-01   2.83209449e-01]
 [  5.81756397e-02   1.44503715e-01  -2.89540808e-03 ...,  -2.22652955e-01
    1.62939902e+00   1.13253277e-01]
 [ -6.03617910e-02   2.61839696e-01   4.68010944e-01 ...,   2.37686406e-01
   -3.05852971e-01   9.56341438e-01]
 ..., 
 [ -1.84188351e-01  -2.38443712e-01  -3.85709361e-01 ...,   9.12458031e-02
   -5.95097232e-01  -3.28054144e-01]
 [ -2.75080108e-01  -1.82561350e-01  -1.81245085e-01 ...,  -1.17487661e-01
   -1.36813245e-01  -3.55178630e-01]
 [  3.90769210e-02   8.41697039e-02  -3.97226952e-02 ...,   5.32695645e-02
    2.90684185e+00  -7.57103635e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.16301855]
 [-0.95111337]
 [-1.19134249]
 [-0.768453  ]
 [-0.05978342]
 [ 2.65196412]
 [-0.05298841]
 [-1.1026047 ]
 [-0.52882533]
 [ 1.0304965 ]
 [-0.09475523]
 [ 0.141554  ]
 [-0.09949326]
 [-1.00795793]
 [-0.30324648]
 [ 0.86719037]
 [-0.83815001]
 [-0.79534243]
 [-0.62009966]
 [ 0.14148529]
 [-0.35215706]
 [ 4.49088177]
 [-0.94808279]
 [-1.64805137]
 [ 0.38369566]
 [-0.30514058]
 [ 4.31782224]
 [-1.92531913]]
[[-0.0195032  -0.30835877  0.26740084 ..., -0.23313356 -0.32356784
   0.28233083]
 [ 0.05814998  0.14435938 -0.00305544 ..., -0.22269866  1.62945807
   0.11315324]
 [-0.0604054   0.26155256  0.46739841 ...,  0.23760864 -0.3066305
   0.95490104]
 ..., 
 [-0.18420056 -0.23849613 -0.38588383 ...,  0.09122714 -0.59486242
  -0.3281332 ]
 [-0.27505368 -0.18241752 -0.18109616 ..., -0.11744038 -0.13719384
  -0.35506084]
 [ 0.03900035  0.0837244  -0.04014543 ...,  0.05311945  2.90692234
  -0.07609618]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16660229]
 [-0.95454335]
 [-1.19434787]
 [-0.77081859]
 [-0.06225911]
 [ 2.64762631]
 [-0.05649707]
 [-1.10353187]
 [-0.53272328]
 [ 1.02883907]
 [-0.09761674]
 [ 0.13845173]
 [-0.10363558]
 [-1.01216835]
 [-0.30705515]
 [ 0.86339255]
 [-0.84153406]
 [-0.79826517]
 [-0.62313321]
 [ 0.13855362]
 [-0.35554638]
 [ 4.49007399]
 [-0.95056485]
 [-1.6490609 ]
 [ 0.3802901 ]
 [-0.30843256]
 [ 4.31232302]
 [-1.92788589]]
[[ -1.92755994e-02  -3.07083560e-01   2.69039595e-01 ...,  -2.32717191e-01
   -3.26857430e-01   2.84490382e-01]
 [  5.82118135e-02   1.44685016e-01  -2.65035060e-03 ...,  -2.22582769e-01
    1.62923510e+00   1.13887062e-01]
 [ -6.00551704e-02   2.63516369e-01   4.69504827e-01 ...,   2.38268049e-01
   -3.10349522e-01   9.59023203e-01]
 ..., 
 [ -1.84127042e-01  -2.38072485e-01  -3.85401854e-01 ...,   9.13650598e-02
   -5.95630175e-01  -3.27644346e-01]
 [ -2.74989340e-01  -1.82082276e-01  -1.80653520e-01 ...,  -1.17335093e-01
   -1.38123322e-01  -3.54628127e-01]
 [  3.90574555e-02   8.40361355e-02  -3.97401200e-02 ...,   5.32188379e-02
    2.90678004e+00  -7.53463701e-02]]
Progress: 80.9% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.16212594]
 [-0.95071528]
 [-1.19305464]
 [-0.76611164]
 [-0.05813615]
 [ 2.6504462 ]
 [-0.05272967]
 [-1.09949264]
 [-0.52936596]
 [ 1.03041407]
 [-0.09489553]
 [ 0.14222459]
 [-0.09954086]
 [-1.01030535]
 [-0.30315058]
 [ 0.86817629]
 [-0.8383302 ]
 [-0.79722288]
 [-0.62007658]
 [ 0.14264906]
 [-0.35209299]
 [ 4.48977811]
 [-0.9468538 ]
 [-1.64535331]
 [ 0.38328732]
 [-0.30416848]
 [ 4.31833173]
 [-1.92651868]]
[[ -1.94080985e-02  -3.07779777e-01   2.68427895e-01 ...,  -2.32972418e-01
   -3.24587782e-01   2.83364700e-01]
 [  5.83208951e-02   1.45333992e-01  -1.94597024e-03 ...,  -2.22402177e-01
    1.62896066e+00   1.15184783e-01]
 [ -6.00779594e-02   2.63397812e-01   4.68692769e-01 ...,   2.38232045e-01
   -3.09504121e-01   9.57996958e-01]
 ..., 
 [ -1.84213512e-01  -2.38555195e-01  -3.85708211e-01 ...,   9.12130224e-02
   -5.94546172e-01  -3.28060945e-01]
 [ -2.74884729e-01  -1.81491638e-01  -1.80050967e-01 ...,  -1.17156686e-01
   -1.38697797e-01  -3.54111290e-01]
 [  3.90230538e-02   8.38147105e-02  -3.98122266e-02 ...,   5.31454945e-02
    2.90676904e+00  -7.56434180e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1627334 ]
 [-0.95144141]
 [-1.19339122]
 [-0.76728155]
 [-0.05953691]
 [ 2.64974091]
 [-0.05369448]
 [-1.10059053]
 [-0.5296645 ]
 [ 1.0313911 ]
 [-0.09622874]
 [ 0.14131641]
 [-0.10010892]
 [-1.01029965]
 [-0.30391088]
 [ 0.86652174]
 [-0.83867045]
 [-0.79665595]
 [-0.62073984]
 [ 0.14171768]
 [-0.35195261]
 [ 4.48965384]
 [-0.94681932]
 [-1.64593092]
 [ 0.38263704]
 [-0.30543878]
 [ 4.31756195]
 [-1.9267519 ]]
[[ -1.92612505e-02  -3.06920487e-01   2.69233359e-01 ...,  -2.32695640e-01
   -3.26318129e-01   2.84134812e-01]
 [  5.83461422e-02   1.45479022e-01  -1.79139239e-03 ...,  -2.22358497e-01
    1.62890057e+00   1.15302615e-01]
 [ -6.01154960e-02   2.63129131e-01   4.68571957e-01 ...,   2.38154872e-01
   -3.11616609e-01   9.58032520e-01]
 ..., 
 [ -1.84237923e-01  -2.38697764e-01  -3.85795593e-01 ...,   9.11536785e-02
   -5.93880641e-01  -3.28649065e-01]
 [ -2.74843346e-01  -1.81264732e-01  -1.79993885e-01 ...,  -1.17072538e-01
   -1.39772363e-01  -3.53959782e-01]
 [  3.90140862e-02   8.37594011e-02  -4.00006328e-02 ...,   5.31270477e-02
    2.90674699e+00  -7.57154427e-02]]
Progress: 80.9% ... Training loss: 0.060 ... Validation loss: 0.136[[-0.16213436]
 [-0.95198736]
 [-1.1955405 ]
 [-0.76536898]
 [-0.05845594]
 [ 2.65048149]
 [-0.05300407]
 [-1.09873914]
 [-0.53175834]
 [ 1.03004222]
 [-0.0959681 ]
 [ 0.14186187]
 [-0.09917729]
 [-1.00968686]
 [-0.30458355]
 [ 0.8661954 ]
 [-0.83918204]
 [-0.79760138]
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 [ 0.14240641]
 [-0.35227733]
 [ 4.48911193]
 [-0.94420238]
 [-1.64519391]
 [ 0.38271856]
 [-0.30604415]
 [ 4.31794994]
 [-1.92711089]]
[[ -1.92684558e-02  -3.06966579e-01   2.69632527e-01 ...,  -2.32709986e-01
   -3.26306237e-01   2.84726739e-01]
 [  5.83537626e-02   1.45522130e-01  -1.80372973e-03 ...,  -2.22344426e-01
    1.62891052e+00   1.15276001e-01]
 [ -5.98571142e-02   2.64556546e-01   4.69670180e-01 ...,   2.38608550e-01
   -3.17568190e-01   9.59432021e-01]
 ..., 
 [ -1.84093431e-01  -2.37867523e-01  -3.84989155e-01 ...,   9.14193284e-02
   -5.95900295e-01  -3.27799968e-01]
 [ -2.74884363e-01  -1.81491237e-01  -1.79879593e-01 ...,  -1.17151626e-01
   -1.38564340e-01  -3.54244590e-01]
 [  3.89799067e-02   8.35606087e-02  -4.01615186e-02 ...,   5.30636327e-02
    2.90684367e+00  -7.57932354e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16086648]
 [-0.95176849]
 [-1.19563457]
 [-0.7645552 ]
 [-0.05780423]
 [ 2.65124143]
 [-0.05234417]
 [-1.09814354]
 [-0.53120699]
 [ 1.03017935]
 [-0.09444114]
 [ 0.14265334]
 [-0.09947464]
 [-1.00969655]
 [-0.30414093]
 [ 0.86701214]
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 [-0.79705454]
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 [ 0.1424599 ]
 [-0.35235292]
 [ 4.4892935 ]
 [-0.94349696]
 [-1.64463159]
 [ 0.38369926]
 [-0.30587118]
 [ 4.31923461]
 [-1.9268207 ]]
[[ -1.91971576e-02  -3.06546119e-01   2.69652061e-01 ...,  -2.32568437e-01
   -3.27496673e-01   2.85226346e-01]
 [  5.83595005e-02   1.45550270e-01  -1.78707757e-03 ...,  -2.22335930e-01
    1.62890198e+00   1.15289655e-01]
 [ -5.98824133e-02   2.64424706e-01   4.69703033e-01 ...,   2.38555095e-01
   -3.17574195e-01   9.58857519e-01]
 ..., 
 [ -1.84097102e-01  -2.37905072e-01  -3.85094370e-01 ...,   9.14152135e-02
   -5.96290531e-01  -3.28116116e-01]
 [ -2.74886650e-01  -1.81474075e-01  -1.80069487e-01 ...,  -1.17151312e-01
   -1.38226232e-01  -3.54466812e-01]
 [  3.89665412e-02   8.34815801e-02  -4.01893462e-02 ...,   5.30359502e-02
    2.90687966e+00  -7.59410578e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15987933]
 [-0.95027741]
 [-1.19419264]
 [-0.76437173]
 [-0.05728337]
 [ 2.65207624]
 [-0.05099872]
 [-1.09884364]
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 [ 1.03107125]
 [-0.09352584]
 [ 0.14373906]
 [-0.09796906]
 [-1.00826348]
 [-0.30303942]
 [ 0.86802201]
 [-0.83695349]
 [-0.79580493]
 [-0.62141328]
 [ 0.14382698]
 [-0.35187616]
 [ 4.48951258]
 [-0.9431231 ]
 [-1.64512441]
 [ 0.38516685]
 [-0.30450368]
 [ 4.32078199]
 [-1.92557706]]
[[ -1.92813038e-02  -3.07056031e-01   2.69296355e-01 ...,  -2.32714348e-01
   -3.26443837e-01   2.84560617e-01]
 [  5.83449209e-02   1.45490050e-01  -1.72534567e-03 ...,  -2.22367944e-01
    1.62915939e+00   1.15259808e-01]
 [ -6.00586968e-02   2.63408065e-01   4.68461499e-01 ...,   2.38255354e-01
   -3.15771445e-01   9.57121466e-01]
 ..., 
 [ -1.84160885e-01  -2.38278720e-01  -3.85446414e-01 ...,   9.13024026e-02
   -5.95016489e-01  -3.28869136e-01]
 [ -2.74848601e-01  -1.81306939e-01  -1.79885511e-01 ...,  -1.17090516e-01
   -1.38737006e-01  -3.54535458e-01]
 [  3.88939161e-02   8.30529342e-02  -4.03813181e-02 ...,   5.29028970e-02
    2.90704270e+00  -7.68361004e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16087647]
 [-0.95201538]
 [-1.19406303]
 [-0.76650134]
 [-0.05861842]
 [ 2.65043521]
 [-0.05291486]
 [-1.10012056]
 [-0.53092789]
 [ 1.03220354]
 [-0.09468327]
 [ 0.14243386]
 [-0.10010496]
 [-1.00947273]
 [-0.30481395]
 [ 0.86653255]
 [-0.83804146]
 [-0.79479592]
 [-0.6219394 ]
 [ 0.1426926 ]
 [-0.3528823 ]
 [ 4.48856094]
 [-0.9437887 ]
 [-1.64498395]
 [ 0.38400104]
 [-0.30663488]
 [ 4.31858161]
 [-1.92661158]]
[[ -1.91636300e-02  -3.06314351e-01   2.69915827e-01 ...,  -2.32506487e-01
   -3.28736061e-01   2.85442253e-01]
 [  5.83493228e-02   1.45517169e-01  -1.77631562e-03 ...,  -2.22368193e-01
    1.62937927e+00   1.15315130e-01]
 [ -5.99307932e-02   2.64269425e-01   4.69981918e-01 ...,   2.38517796e-01
   -3.16074463e-01   9.58134028e-01]
 ..., 
 [ -1.84129480e-01  -2.38122017e-01  -3.85199397e-01 ...,   9.13597636e-02
   -5.96139625e-01  -3.28443049e-01]
 [ -2.74782636e-01  -1.80903200e-01  -1.79586684e-01 ...,  -1.16994332e-01
   -1.39764728e-01  -3.53911913e-01]
 [  3.88999598e-02   8.31138604e-02  -4.03130686e-02 ...,   5.29211985e-02
    2.90701649e+00  -7.71524733e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15992057]
 [-0.95131125]
 [-1.19341734]
 [-0.7658371 ]
 [-0.05759318]
 [ 2.64981095]
 [-0.05260563]
 [-1.09944715]
 [-0.53017185]
 [ 1.03329138]
 [-0.09421234]
 [ 0.14288544]
 [-0.09953803]
 [-1.00965968]
 [-0.30399099]
 [ 0.86778302]
 [-0.83732188]
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 [ 0.14353013]
 [-0.35163252]
 [ 4.48870509]
 [-0.94366325]
 [-1.64405385]
 [ 0.38428385]
 [-0.30612852]
 [ 4.31981736]
 [-1.92686245]]
[[ -1.91049548e-02  -3.05939274e-01   2.70186149e-01 ...,  -2.32397708e-01
   -3.29216293e-01   2.86322643e-01]
 [  5.83782089e-02   1.45669529e-01  -1.64752512e-03 ...,  -2.22319801e-01
    1.62926519e+00   1.15379455e-01]
 [ -5.98704185e-02   2.64605329e-01   4.70384736e-01 ...,   2.38623029e-01
   -3.17088632e-01   9.58700905e-01]
 ..., 
 [ -1.84102547e-01  -2.37956786e-01  -3.84931445e-01 ...,   9.14126719e-02
   -5.96772100e-01  -3.28167461e-01]
 [ -2.74746855e-01  -1.80693878e-01  -1.79250079e-01 ...,  -1.16934329e-01
   -1.39739280e-01  -3.53383022e-01]
 [  3.88979626e-02   8.30970535e-02  -4.02445682e-02 ...,   5.29162018e-02
    2.90697398e+00  -7.72024677e-02]]
Progress: 80.9% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.15420308]
 [-0.94610734]
 [-1.18933279]
 [-0.76147739]
 [-0.0539286 ]
 [ 2.65435138]
 [-0.04754937]
 [-1.09816937]
 [-0.52427464]
 [ 1.0361899 ]
 [-0.08979199]
 [ 0.14731913]
 [-0.09410367]
 [-1.00501303]
 [-0.29868394]
 [ 0.87320847]
 [-0.8316547 ]
 [-0.7898142 ]
 [-0.61640392]
 [ 0.14800003]
 [-0.34726954]
 [ 4.4906124 ]
 [-0.93986956]
 [-1.64228975]
 [ 0.38883389]
 [-0.30092314]
 [ 4.32860838]
 [-1.92313534]]
[[ -1.93238049e-02  -3.07251516e-01   2.68937491e-01 ...,  -2.32806634e-01
   -3.26676828e-01   2.84105092e-01]
 [  5.83954528e-02   1.45764482e-01  -1.49375698e-03 ...,  -2.22288157e-01
    1.62919437e+00   1.15512466e-01]
 [ -6.03459183e-02   2.61780905e-01   4.67222725e-01 ...,   2.37731693e-01
   -3.11598814e-01   9.54162586e-01]
 ..., 
 [ -1.84220379e-01  -2.38633791e-01  -3.85630556e-01 ...,   9.11954654e-02
   -5.94626241e-01  -3.28865113e-01]
 [ -2.74736333e-01  -1.80637379e-01  -1.79307951e-01 ...,  -1.16926271e-01
   -1.39301078e-01  -3.53688406e-01]
 [  3.88461800e-02   8.28018213e-02  -4.05031809e-02 ...,   5.28205186e-02
    2.90696985e+00  -7.76404063e-02]]
Progress: 80.9% ... Training loss: 0.069 ... Validation loss: 0.149[[-0.16459693]
 [-0.9542968 ]
 [-1.19698776]
 [-0.76989302]
 [-0.06151936]
 [ 2.65050777]
 [-0.0556501 ]
 [-1.10450463]
 [-0.53356881]
 [ 1.03008228]
 [-0.09829067]
 [ 0.13868082]
 [-0.10279141]
 [-1.01092314]
 [-0.30764551]
 [ 0.86287526]
 [-0.8415502 ]
 [-0.79856026]
 [-0.62523103]
 [ 0.13935201]
 [-0.35607076]
 [ 4.48983951]
 [-0.94701757]
 [-1.65089377]
 [ 0.38146356]
 [-0.3089758 ]
 [ 4.31265433]
 [-1.92820418]]
[[ -1.90067756e-02  -3.05323644e-01   2.71070892e-01 ...,  -2.32208818e-01
   -3.29359806e-01   2.86909908e-01]
 [  5.84029387e-02   1.45808484e-01  -1.50732344e-03 ...,  -2.22272779e-01
    1.62918016e+00   1.15418859e-01]
 [ -6.01608573e-02   2.63065946e-01   4.68761287e-01 ...,   2.38126917e-01
   -3.11657028e-01   9.57223048e-01]
 ..., 
 [ -1.84096525e-01  -2.37898740e-01  -3.84885278e-01 ...,   9.14296434e-02
   -5.96932051e-01  -3.27769632e-01]
 [ -2.74699610e-01  -1.80435511e-01  -1.79120871e-01 ...,  -1.16862817e-01
   -1.38674110e-01  -3.53857719e-01]
 [  3.88949396e-02   8.30878222e-02  -4.01509938e-02 ...,   5.29082397e-02
    2.90691245e+00  -7.73078929e-02]]
Progress: 80.9% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16388258]
 [-0.95341376]
 [-1.19503591]
 [-0.76898159]
 [-0.06056435]
 [ 2.6474602 ]
 [-0.05597879]
 [-1.10256551]
 [-0.53269303]
 [ 1.03165566]
 [-0.09738288]
 [ 0.1395294 ]
 [-0.10314998]
 [-1.01345406]
 [-0.30627484]
 [ 0.86453695]
 [-0.83988688]
 [-0.79780973]
 [-0.62273377]
 [ 0.13999204]
 [-0.35485863]
 [ 4.48825543]
 [-0.94836672]
 [-1.64812884]
 [ 0.38084516]
 [-0.30789533]
 [ 4.31478459]
 [-1.9296741 ]]
[[ -1.88495964e-02  -3.04479705e-01   2.71983584e-01 ...,  -2.31942865e-01
   -3.31437177e-01   2.88704632e-01]
 [  5.84224616e-02   1.45910173e-01  -1.37245969e-03 ...,  -2.22238735e-01
    1.62904260e+00   1.15601745e-01]
 [ -5.98968061e-02   2.64562817e-01   4.70174945e-01 ...,   2.38611698e-01
   -3.16941039e-01   9.60068376e-01]
 ..., 
 [ -1.84116399e-01  -2.38030329e-01  -3.84963378e-01 ...,   9.13898719e-02
   -5.96884402e-01  -3.27816952e-01]
 [ -2.74588907e-01  -1.79813283e-01  -1.78368639e-01 ...,  -1.16670059e-01
   -1.39900137e-01  -3.52428502e-01]
 [  3.88268288e-02   8.26897819e-02  -4.06910227e-02 ...,   5.27770557e-02
    2.90710974e+00  -7.80656210e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15874055]
 [-0.9487677 ]
 [-1.19089987]
 [-0.76461691]
 [-0.05637241]
 [ 2.64988341]
 [-0.05119541]
 [-1.09966934]
 [-0.52753186]
 [ 1.03571192]
 [-0.09305328]
 [ 0.14389603]
 [-0.09758357]
 [-1.00907533]
 [-0.30129982]
 [ 0.86969366]
 [-0.83472337]
 [-0.79310268]
 [-0.61898796]
 [ 0.14463149]
 [-0.35031593]
 [ 4.48975938]
 [-0.94411909]
 [-1.64413082]
 [ 0.3845925 ]
 [-0.30340017]
 [ 4.32280474]
 [-1.92678202]]
[[ -1.90102329e-02  -3.05417361e-01   2.70795564e-01 ...,  -2.32227280e-01
   -3.28877376e-01   2.87646483e-01]
 [  5.84274975e-02   1.45939444e-01  -1.33692005e-03 ...,  -2.22229260e-01
    1.62897156e+00   1.15641253e-01]
 [ -6.00900490e-02   2.63494107e-01   4.68966522e-01 ...,   2.38264593e-01
   -3.12528748e-01   9.57414678e-01]
 ..., 
 [ -1.84173372e-01  -2.38361568e-01  -3.85274929e-01 ...,   9.12884344e-02
   -5.95683636e-01  -3.28603500e-01]
 [ -2.74729455e-01  -1.80581769e-01  -1.79189972e-01 ...,  -1.16918353e-01
   -1.36968700e-01  -3.53548401e-01]
 [  3.88502121e-02   8.28290754e-02  -4.06729755e-02 ...,   5.28249421e-02
    2.90711846e+00  -7.79820660e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.15780323]
 [-0.94726751]
 [-1.1899397 ]
 [-0.76408901]
 [-0.05559903]
 [ 2.65234452]
 [-0.05005996]
 [-1.10004122]
 [-0.52703406]
 [ 1.03500816]
 [-0.09215901]
 [ 0.1446428 ]
 [-0.09582082]
 [-1.00709011]
 [-0.29996316]
 [ 0.87030175]
 [-0.83331416]
 [-0.79252194]
 [-0.61849786]
 [ 0.14570423]
 [-0.35047388]
 [ 4.48990412]
 [-0.94306871]
 [-1.64452831]
 [ 0.38620427]
 [-0.30187931]
 [ 4.32536638]
 [-1.92608499]]
[[ -1.91616236e-02  -3.06352528e-01   2.70308714e-01 ...,  -2.32523576e-01
   -3.26781497e-01   2.86154364e-01]
 [  5.84295904e-02   1.45938526e-01  -1.34255275e-03 ...,  -2.22234287e-01
    1.62909375e+00   1.15353484e-01]
 [ -6.02632649e-02   2.62495247e-01   4.68138957e-01 ...,   2.37958296e-01
   -3.10120064e-01   9.55997355e-01]
 ..., 
 [ -1.84098757e-01  -2.37956420e-01  -3.84928774e-01 ...,   9.14245802e-02
   -5.96642296e-01  -3.28371935e-01]
 [ -2.74668611e-01  -1.80238998e-01  -1.78846094e-01 ...,  -1.16820510e-01
   -1.38670648e-01  -3.53431288e-01]
 [  3.86792767e-02   8.18237434e-02  -4.15819400e-02 ...,   5.25038248e-02
    2.90751186e+00  -7.92940378e-02]]
Progress: 81.0% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16492175]
 [-0.95342993]
 [-1.19525905]
 [-0.77106413]
 [-0.06172571]
 [ 2.64974528]
 [-0.05620593]
 [-1.1058071 ]
 [-0.53243154]
 [ 1.03180697]
 [-0.09806823]
 [ 0.13852685]
 [-0.1033004 ]
 [-1.01108492]
 [-0.30702861]
 [ 0.86300508]
 [-0.84057081]
 [-0.79815121]
 [-0.62356847]
 [ 0.13925855]
 [-0.35650985]
 [ 4.48814251]
 [-0.94855639]
 [-1.6517574 ]
 [ 0.38144705]
 [-0.3082934 ]
 [ 4.31274442]
 [-1.92870374]]
[[ -1.89020149e-02  -3.04835899e-01   2.71868377e-01 ...,  -2.32037024e-01
   -3.28114775e-01   2.88520668e-01]
 [  5.84187839e-02   1.45863409e-01  -1.44298379e-03 ...,  -2.22258107e-01
    1.62947904e+00   1.15195108e-01]
 [ -6.02475836e-02   2.62555844e-01   4.69063840e-01 ...,   2.37990071e-01
   -3.09441547e-01   9.57465026e-01]
 ..., 
 [ -1.84075161e-01  -2.37822877e-01  -3.84781170e-01 ...,   9.14728413e-02
   -5.97149234e-01  -3.27917215e-01]
 [ -2.74446026e-01  -1.78912582e-01  -1.77561033e-01 ...,  -1.16403256e-01
   -1.40724296e-01  -3.51525317e-01]
 [  3.87776577e-02   8.24115809e-02  -4.09762825e-02 ...,   5.26864112e-02
    2.90743256e+00  -7.87036799e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.16147315]
 [-0.95034037]
 [-1.19268731]
 [-0.76836815]
 [-0.05844062]
 [ 2.65037565]
 [-0.05314999]
 [-1.10297   ]
 [-0.52914711]
 [ 1.03451919]
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 [ 0.14160325]
 [-0.0998301 ]
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 [-0.30392109]
 [ 0.86672125]
 [-0.83780506]
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 [ 0.14274559]
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 [ 4.48976855]
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 [ 0.38381524]
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 [ 4.31730451]
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[[ -1.90726293e-02  -3.05778916e-01   2.71040505e-01 ...,  -2.32339595e-01
   -3.26282971e-01   2.87432331e-01]
 [  5.85094768e-02   1.46387037e-01  -9.22388847e-04 ...,  -2.22090693e-01
    1.62825538e+00   1.15999924e-01]
 [ -6.02467513e-02   2.62584220e-01   4.68800818e-01 ...,   2.38026430e-01
   -3.06052276e-01   9.56532884e-01]
 ..., 
 [ -1.84170058e-01  -2.38366339e-01  -3.85303268e-01 ...,   9.13053040e-02
   -5.95718049e-01  -3.28823316e-01]
 [ -2.74517127e-01  -1.79319394e-01  -1.77766251e-01 ...,  -1.16533817e-01
   -1.38950248e-01  -3.52493237e-01]
 [  3.87553554e-02   8.22668005e-02  -4.11456642e-02 ...,   5.26290232e-02
    2.90743443e+00  -7.88444656e-02]]
Progress: 81.0% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16279108]
 [-0.95205389]
 [-1.19419017]
 [-0.76948193]
 [-0.05989931]
 [ 2.64890544]
 [-0.05448261]
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 [ 1.03498062]
 [-0.09611862]
 [ 0.14031984]
 [-0.10121771]
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 [-0.30565632]
 [ 0.8654652 ]
 [-0.83949634]
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 [ 0.14126116]
 [-0.35461778]
 [ 4.49006462]
 [-0.94571231]
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 [ 0.38209877]
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 [ 4.31450642]
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[[ -1.89066461e-02  -3.04786033e-01   2.71904369e-01 ...,  -2.32042654e-01
   -3.25581828e-01   2.89607769e-01]
 [  5.85732127e-02   1.46765824e-01  -6.23842925e-04 ...,  -2.21972751e-01
    1.62840916e+00   1.16729201e-01]
 [ -6.01133068e-02   2.63313514e-01   4.69167050e-01 ...,   2.38271143e-01
   -3.06434076e-01   9.57702404e-01]
 ..., 
 [ -1.84232548e-01  -2.38726170e-01  -3.85574566e-01 ...,   9.11948073e-02
   -5.94943039e-01  -3.29317649e-01]
 [ -2.74469037e-01  -1.79039784e-01  -1.77743557e-01 ...,  -1.16458939e-01
   -1.39581290e-01  -3.52279773e-01]
 [  3.88777566e-02   8.29927822e-02  -4.03591932e-02 ...,   5.28532089e-02
    2.90737066e+00  -7.76384959e-02]]
Progress: 81.0% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1594367 ]
 [-0.94776967]
 [-1.19182438]
 [-0.76560274]
 [-0.0562566 ]
 [ 2.65138816]
 [-0.05059232]
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 [ 1.03723524]
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 [ 0.14361588]
 [-0.09730562]
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 [ 0.14445939]
 [-0.35146739]
 [ 4.49040731]
 [-0.94367006]
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 [ 0.38469551]
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 [ 4.32033102]
 [-1.92648037]]
[[ -1.89397746e-02  -3.05011867e-01   2.71573808e-01 ...,  -2.32110962e-01
   -3.24708698e-01   2.88986401e-01]
 [  5.85175885e-02   1.46438841e-01  -7.54138806e-04 ...,  -2.22071426e-01
    1.62842045e+00   1.16374295e-01]
 [ -6.02928919e-02   2.62309898e-01   4.68059156e-01 ...,   2.37924043e-01
   -3.05029248e-01   9.55430305e-01]
 ..., 
 [ -1.84228181e-01  -2.38692838e-01  -3.85624678e-01 ...,   9.12029868e-02
   -5.94936625e-01  -3.29383479e-01]
 [ -2.74468612e-01  -1.79083122e-01  -1.77445171e-01 ...,  -1.16468388e-01
   -1.40577536e-01  -3.52423805e-01]
 [  3.87895351e-02   8.24779259e-02  -4.09007961e-02 ...,   5.26866355e-02
    2.90797356e+00  -7.87664214e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16286667]
 [-0.95109473]
 [-1.19348598]
 [-0.76901715]
 [-0.05935413]
 [ 2.64896095]
 [-0.05422031]
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 [ 1.03574374]
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 [ 0.14055629]
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 [ 0.86658481]
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 [ 0.14128514]
 [-0.35482002]
 [ 4.49014587]
 [-0.94748279]
 [-1.65051455]
 [ 0.38172249]
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 [ 4.31467891]
 [-1.92828165]]
[[ -1.88449925e-02  -3.04481214e-01   2.71896209e-01 ...,  -2.31939346e-01
   -3.26687495e-01   2.90277535e-01]
 [  5.85358004e-02   1.46536521e-01  -6.16464511e-04 ...,  -2.22038506e-01
    1.62831021e+00   1.16552062e-01]
 [ -6.01764274e-02   2.62965274e-01   4.68990531e-01 ...,   2.38163161e-01
   -3.07524828e-01   9.56976238e-01]
 ..., 
 [ -1.84215752e-01  -2.38635832e-01  -3.85654444e-01 ...,   9.12291349e-02
   -5.94968049e-01  -3.29448585e-01]
 [ -2.74366205e-01  -1.78512228e-01  -1.77065286e-01 ...,  -1.16287358e-01
   -1.41446015e-01  -3.51754877e-01]
 [  3.89121263e-02   8.31697614e-02  -4.01947901e-02 ...,   5.29065487e-02
    2.90780824e+00  -7.80223048e-02]]
Progress: 81.0% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.16644995]
 [-0.95405564]
 [-1.19509968]
 [-0.77330147]
 [-0.06263041]
 [ 2.64837297]
 [-0.05694696]
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 [ 1.03410305]
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 [ 0.13744232]
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 [ 0.86303676]
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 [ 0.13853565]
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 [ 4.49023187]
 [-0.95139887]
 [-1.65388815]
 [ 0.37982462]
 [-0.30864718]
 [ 4.30913032]
 [-1.92953856]]
[[ -1.88827075e-02  -3.04674888e-01   2.71588862e-01 ...,  -2.32000756e-01
   -3.27468330e-01   2.89766875e-01]
 [  5.85418197e-02   1.46577734e-01  -6.37512376e-04 ...,  -2.22028375e-01
    1.62809041e+00   1.16498571e-01]
 [ -6.02606051e-02   2.62586885e-01   4.68824378e-01 ...,   2.38018266e-01
   -3.06259261e-01   9.57684577e-01]
 ..., 
 [ -1.84065803e-01  -2.37796529e-01  -3.85173605e-01 ...,   9.14927729e-02
   -5.97510882e-01  -3.28360164e-01]
 [ -2.74379127e-01  -1.78562662e-01  -1.77035194e-01 ...,  -1.16307808e-01
   -1.40696262e-01  -3.52056873e-01]
 [  3.88833972e-02   8.30098334e-02  -4.04820666e-02 ...,   5.28647120e-02
    2.90794617e+00  -7.80026865e-02]]
Progress: 81.0% ... Training loss: 0.064 ... Validation loss: 0.135[[-0.15722509]
 [-0.94668593]
 [-1.18633292]
 [-0.76790032]
 [-0.05709245]
 [ 2.65581635]
 [-0.04913882]
 [-1.10452948]
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 [ 1.03945264]
 [-0.09337997]
 [ 0.14525959]
 [-0.09539581]
 [-1.00426402]
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 [ 0.87190234]
 [-0.83310456]
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 [ 0.14661867]
 [-0.34948041]
 [ 4.49241292]
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 [ 4.32420465]
 [-1.92316778]]
[[ -1.94747282e-02  -3.07969904e-01   2.68158296e-01 ...,  -2.33021018e-01
   -3.22126787e-01   2.83672679e-01]
 [  5.85219571e-02   1.46464151e-01  -7.96936151e-04 ...,  -2.22061170e-01
    1.62820143e+00   1.16168931e-01]
 [ -6.07990457e-02   2.59513246e-01   4.64847648e-01 ...,   2.37062392e-01
   -3.01048874e-01   9.50850016e-01]
 ..., 
 [ -1.84092058e-01  -2.37936927e-01  -3.85458048e-01 ...,   9.14465441e-02
   -5.96371490e-01  -3.28668880e-01]
 [ -2.74509524e-01  -1.79285076e-01  -1.77950835e-01 ...,  -1.16528253e-01
   -1.38690434e-01  -3.53518986e-01]
 [  3.87132738e-02   8.20414449e-02  -4.13982459e-02 ...,   5.25704293e-02
    2.90824204e+00  -7.98437786e-02]]
Progress: 81.0% ... Training loss: 0.068 ... Validation loss: 0.144[[-0.16864334]
 [-0.95631813]
 [-1.19495484]
 [-0.77646839]
 [-0.06522768]
 [ 2.64875095]
 [-0.05884202]
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 [ 1.03269393]
 [-0.10232229]
 [ 0.13609607]
 [-0.10567618]
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 [ 0.86046722]
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 [ 0.13762095]
 [-0.35873091]
 [ 4.4904387 ]
 [-0.95287392]
 [-1.65538073]
 [ 0.37895514]
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 [ 4.30741267]
 [-1.92968268]]
[[ -1.90760557e-02  -3.05689447e-01   2.70907509e-01 ...,  -2.32288238e-01
   -3.28287017e-01   2.87914712e-01]
 [  5.85167920e-02   1.46420963e-01  -8.31698145e-04 ...,  -2.22071823e-01
    1.62831019e+00   1.16157672e-01]
 [ -6.02751774e-02   2.62673608e-01   4.68666552e-01 ...,   2.38059904e-01
   -3.10839436e-01   9.57809670e-01]
 ..., 
 [ -1.83920707e-01  -2.36983001e-01  -3.84699145e-01 ...,   9.17690153e-02
   -5.99544455e-01  -3.27539136e-01]
 [ -2.74440076e-01  -1.78865005e-01  -1.77424791e-01 ...,  -1.16410887e-01
   -1.39126984e-01  -3.52961153e-01]
 [  3.87955652e-02   8.25459064e-02  -4.08609686e-02 ...,   5.27325009e-02
    2.90810639e+00  -7.91532966e-02]]
Progress: 81.0% ... Training loss: 0.066 ... Validation loss: 0.137[[-0.1604197 ]
 [-0.94999245]
 [-1.19126101]
 [-0.76787646]
 [-0.05746507]
 [ 2.65080266]
 [-0.05181676]
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 [ 1.03733165]
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 [ 0.14344945]
 [-0.09753353]
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 [-0.30180332]
 [ 0.8690984 ]
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 [ 0.14483176]
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 [ 4.49136888]
 [-0.94602819]
 [-1.64581064]
 [ 0.3839828 ]
 [-0.30470118]
 [ 4.3196047 ]
 [-1.92775287]]
[[ -1.93098262e-02  -3.06873178e-01   2.69929218e-01 ...,  -2.32687889e-01
   -3.22999319e-01   2.87164630e-01]
 [  5.84822116e-02   1.46257499e-01  -9.30675199e-04 ...,  -2.22132533e-01
    1.62868835e+00   1.15991522e-01]
 [ -6.00236503e-02   2.64057091e-01   4.69520932e-01 ...,   2.38523048e-01
   -3.09801534e-01   9.57747505e-01]
 ..., 
 [ -1.84014151e-01  -2.37512086e-01  -3.85251619e-01 ...,   9.15984430e-02
   -5.98521260e-01  -3.27844850e-01]
 [ -2.74588364e-01  -1.79659040e-01  -1.78112393e-01 ...,  -1.16673982e-01
   -1.35754553e-01  -3.54052290e-01]
 [  3.87401295e-02   8.22325732e-02  -4.12259991e-02 ...,   5.26260708e-02
    2.90812882e+00  -7.96769617e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.165242  ]
 [-0.95377123]
 [-1.1965676 ]
 [-0.77025246]
 [-0.05987648]
 [ 2.64720043]
 [-0.05594157]
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 [ 1.03379082]
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 [-1.01417874]
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 [ 0.86447634]
 [-0.84139659]
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 [ 0.14101152]
 [-0.35581037]
 [ 4.49053   ]
 [-0.94970001]
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 [ 0.37966985]
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 [ 4.31337335]
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[[ -1.90846646e-02  -3.05682368e-01   2.71306026e-01 ...,  -2.32287349e-01
   -3.28201687e-01   2.89256995e-01]
 [  5.85194661e-02   1.46473571e-01  -6.96436781e-04 ...,  -2.22064922e-01
    1.62842087e+00   1.16349682e-01]
 [ -5.96800307e-02   2.65968053e-01   4.72096391e-01 ...,   2.39179148e-01
   -3.14254431e-01   9.61973849e-01]
 ..., 
 [ -1.83878744e-01  -2.36747073e-01  -3.84443891e-01 ...,   9.18613277e-02
   -6.01276710e-01  -3.26891895e-01]
 [ -2.74586799e-01  -1.79679566e-01  -1.78035720e-01 ...,  -1.16683082e-01
   -1.36517251e-01  -3.54070456e-01]
 [  3.88295536e-02   8.27302806e-02  -4.06418343e-02 ...,   5.28001374e-02
    2.90814670e+00  -7.88527489e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16224621]
 [-0.95173839]
 [-1.19453806]
 [-0.76736053]
 [-0.05680414]
 [ 2.64616432]
 [-0.05378129]
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 [ 0.14225612]
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 [-0.83858251]
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 [-0.35297028]
 [ 4.49175871]
 [-0.94822312]
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 [ 0.38098611]
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[[ -1.91568887e-02  -3.06085215e-01   2.71091809e-01 ...,  -2.32417095e-01
   -3.24729505e-01   2.89208632e-01]
 [  5.85245612e-02   1.46504140e-01  -6.94388717e-04 ...,  -2.22054440e-01
    1.62827465e+00   1.16555807e-01]
 [ -5.94214153e-02   2.67550481e-01   4.73676820e-01 ...,   2.39676080e-01
   -3.12459536e-01   9.63561444e-01]
 ..., 
 [ -1.84029683e-01  -2.37582941e-01  -3.85286768e-01 ...,   9.15879397e-02
   -5.99112970e-01  -3.27898543e-01]
 [ -2.74658399e-01  -1.80091053e-01  -1.78460548e-01 ...,  -1.16806226e-01
   -1.35359922e-01  -3.54346808e-01]
 [  3.88519657e-02   8.28090316e-02  -4.03369916e-02 ...,   5.28308601e-02
    2.90807311e+00  -7.86683356e-02]]
Progress: 81.0% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.15962792]
 [-0.94973657]
 [-1.1911303 ]
 [-0.76599563]
 [-0.05567582]
 [ 2.64867642]
 [-0.05217112]
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 [ 4.49339586]
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 [-1.92910622]]
[[ -1.92709870e-02  -3.06871927e-01   2.70075052e-01 ...,  -2.32631255e-01
   -3.24734996e-01   2.87238110e-01]
 [  5.85724279e-02   1.46774530e-01  -4.09717695e-04 ...,  -2.21965386e-01
    1.62761926e+00   1.16922940e-01]
 [ -5.98125689e-02   2.65296699e-01   4.71772420e-01 ...,   2.38967303e-01
   -3.10139714e-01   9.60335945e-01]
 ..., 
 [ -1.84016604e-01  -2.37555228e-01  -3.85248894e-01 ...,   9.16139570e-02
   -5.99554367e-01  -3.28265325e-01]
 [ -2.74722931e-01  -1.80464274e-01  -1.79046776e-01 ...,  -1.16935196e-01
   -1.34769557e-01  -3.55238283e-01]
 [  3.88642084e-02   8.28521375e-02  -4.02808843e-02 ...,   5.28544606e-02
    2.90809028e+00  -7.88507154e-02]]
Progress: 81.0% ... Training loss: 0.062 ... Validation loss: 0.141[[-0.16137202]
 [-0.95057108]
 [-1.19244002]
 [-0.76826964]
 [-0.0577996 ]
 [ 2.65149428]
 [-0.05287346]
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 [ 1.03616124]
 [-0.09716689]
 [ 0.14170444]
 [-0.09938182]
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 [ 0.86932756]
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 [ 0.14448219]
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 [ 4.49373942]
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 [-1.64938028]
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 [ 4.31825278]
 [-1.92762619]]
[[ -1.94643990e-02  -3.08072341e-01   2.69079074e-01 ...,  -2.32996974e-01
   -3.22448850e-01   2.85005860e-01]
 [  5.86360434e-02   1.47149653e-01  -3.43334842e-04 ...,  -2.21850518e-01
    1.62755035e+00   1.17481099e-01]
 [ -6.01548591e-02   2.63340117e-01   4.69947173e-01 ...,   2.38345601e-01
   -3.06337070e-01   9.57255926e-01]
 ..., 
 [ -1.83880051e-01  -2.36790287e-01  -3.84699171e-01 ...,   9.18701685e-02
   -6.00643900e-01  -3.27265911e-01]
 [ -2.74780213e-01  -1.80844244e-01  -1.79232491e-01 ...,  -1.17054760e-01
   -1.33410861e-01  -3.55713282e-01]
 [  3.89863101e-02   8.35661100e-02  -3.96361108e-02 ...,   5.30734196e-02
    2.90811514e+00  -7.89582378e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16301281]
 [-0.95159741]
 [-1.19443772]
 [-0.76922802]
 [-0.05947413]
 [ 2.65142157]
 [-0.05364927]
 [-1.10616554]
 [-0.53030248]
 [ 1.03499013]
 [-0.09807988]
 [ 0.13992781]
 [-0.10060296]
 [-1.01108834]
 [-0.30432442]
 [ 0.86633502]
 [-0.83947121]
 [-0.79729184]
 [-0.62330385]
 [ 0.14276382]
 [-0.35530722]
 [ 4.49429178]
 [-0.94867456]
 [-1.65212624]
 [ 0.38160808]
 [-0.30535342]
 [ 4.31633861]
 [-1.92827835]]
[[ -1.93772757e-02  -3.07597829e-01   2.69787378e-01 ...,  -2.32853382e-01
   -3.23955939e-01   2.85768804e-01]
 [  5.86387996e-02   1.47161541e-01  -2.78420530e-04 ...,  -2.21845404e-01
    1.62749471e+00   1.17576628e-01]
 [ -6.02122535e-02   2.63105710e-01   4.69805726e-01 ...,   2.38227731e-01
   -3.07081166e-01   9.57380865e-01]
 ..., 
 [ -1.83900413e-01  -2.36908475e-01  -3.84873375e-01 ...,   9.18341638e-02
   -6.00348169e-01  -3.27421018e-01]
 [ -2.74718098e-01  -1.80478962e-01  -1.79023511e-01 ...,  -1.16954259e-01
   -1.33936415e-01  -3.55398034e-01]
 [  3.90351885e-02   8.38493520e-02  -3.93940040e-02 ...,   5.31616619e-02
    2.90803740e+00  -7.87174737e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16049382]
 [-0.94838062]
 [-1.19303334]
 [-0.7657597 ]
 [-0.0562256 ]
 [ 2.65269918]
 [-0.05093107]
 [-1.10312181]
 [-0.52832718]
 [ 1.03636   ]
 [-0.09551241]
 [ 0.14224954]
 [-0.09778688]
 [-1.00974721]
 [-0.30131474]
 [ 0.86872333]
 [-0.83658659]
 [-0.79602338]
 [-0.62188074]
 [ 0.1448535 ]
 [-0.35314562]
 [ 4.49543618]
 [-0.94630382]
 [-1.64978235]
 [ 0.3835281 ]
 [-0.30236703]
 [ 4.3218027 ]
 [-1.92739619]]
[[ -1.93488342e-02  -3.07460112e-01   2.70029980e-01 ...,  -2.32799083e-01
   -3.25198630e-01   2.86140151e-01]
 [  5.86042632e-02   1.46978201e-01  -3.85477671e-04 ...,  -2.21902953e-01
    1.62766930e+00   1.17535076e-01]
 [ -6.02623738e-02   2.62787126e-01   4.69360766e-01 ...,   2.38148178e-01
   -3.07770569e-01   9.56448390e-01]
 ..., 
 [ -1.83851497e-01  -2.36641191e-01  -3.84636886e-01 ...,   9.19226388e-02
   -6.01571087e-01  -3.26977510e-01]
 [ -2.74911579e-01  -1.81528721e-01  -1.80045364e-01 ...,  -1.17302594e-01
   -1.33447288e-01  -3.56934515e-01]
 [  3.90006468e-02   8.36445769e-02  -3.95769966e-02 ...,   5.30983307e-02
    2.90800231e+00  -7.85696503e-02]]
Progress: 81.1% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.16545137]
 [-0.95212032]
 [-1.19647481]
 [-0.77008044]
 [-0.05995493]
 [ 2.64909574]
 [-0.05478053]
 [-1.10675812]
 [-0.53213408]
 [ 1.0347808 ]
 [-0.10015284]
 [ 0.13852908]
 [-0.10171596]
 [-1.01300709]
 [-0.30517847]
 [ 0.86428567]
 [-0.84147034]
 [-0.79929848]
 [-0.62525777]
 [ 0.14116785]
 [-0.35597571]
 [ 4.49506417]
 [-0.95073412]
 [-1.6536169 ]
 [ 0.38002534]
 [-0.30649105]
 [ 4.31406496]
 [-1.92992735]]
[[ -1.90868079e-02  -3.05968152e-01   2.71441434e-01 ...,  -2.32314076e-01
   -3.28018779e-01   2.88741143e-01]
 [  5.86024734e-02   1.46961571e-01  -4.68431095e-04 ...,  -2.21906671e-01
    1.62763521e+00   1.17545329e-01]
 [ -6.01564012e-02   2.63436504e-01   4.70281022e-01 ...,   2.38357914e-01
   -3.10028730e-01   9.59215354e-01]
 ..., 
 [ -1.83763974e-01  -2.36126834e-01  -3.84181087e-01 ...,   9.20885732e-02
   -6.02972857e-01  -3.26164156e-01]
 [ -2.74910784e-01  -1.81534208e-01  -1.80093931e-01 ...,  -1.17295793e-01
   -1.34027384e-01  -3.57230764e-01]
 [  3.90500365e-02   8.39198092e-02  -3.92572287e-02 ...,   5.31799922e-02
    2.90786612e+00  -7.80937600e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16128576]
 [-0.94861574]
 [-1.19453098]
 [-0.76660885]
 [-0.05717745]
 [ 2.64977933]
 [-0.05153438]
 [-1.10370031]
 [-0.52910843]
 [ 1.03730856]
 [-0.09681594]
 [ 0.1417505 ]
 [-0.09801976]
 [-1.01111071]
 [-0.30189896]
 [ 0.86765395]
 [-0.83778199]
 [-0.79595868]
 [-0.62269343]
 [ 0.14451324]
 [-0.35226887]
 [ 4.49642742]
 [-0.94695142]
 [-1.64902022]
 [ 0.38255366]
 [-0.30389983]
 [ 4.32112637]
 [-1.92828598]]
[[ -1.91967069e-02  -3.06593253e-01   2.70643156e-01 ...,  -2.32507920e-01
   -3.28346461e-01   2.88074672e-01]
 [  5.85729825e-02   1.46794398e-01  -5.80770685e-04 ...,  -2.21957837e-01
    1.62768806e+00   1.17398974e-01]
 [ -6.01214664e-02   2.63609034e-01   4.69810057e-01 ...,   2.38430151e-01
   -3.09113764e-01   9.58941737e-01]
 ..., 
 [ -1.83778410e-01  -2.36205614e-01  -3.84466458e-01 ...,   9.20556261e-02
   -6.01834905e-01  -3.26683991e-01]
 [ -2.74868373e-01  -1.81276836e-01  -1.80132658e-01 ...,  -1.17202845e-01
   -1.35909998e-01  -3.56550297e-01]
 [  3.90127761e-02   8.36622076e-02  -3.94147961e-02 ...,   5.31086652e-02
    2.90796331e+00  -7.84151611e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16323   ]
 [-0.95087109]
 [-1.19605887]
 [-0.76790403]
 [-0.05862203]
 [ 2.64768004]
 [-0.05403198]
 [-1.10437579]
 [-0.53155205]
 [ 1.03532798]
 [-0.0982577 ]
 [ 0.13975498]
 [-0.1012694 ]
 [-1.01388646]
 [-0.30395166]
 [ 0.86521037]
 [-0.83957112]
 [-0.79817521]
 [-0.62425094]
 [ 0.14255972]
 [-0.35479014]
 [ 4.49481904]
 [-0.94901534]
 [-1.64991496]
 [ 0.38030549]
 [-0.30599603]
 [ 4.31751226]
 [-1.92993399]]
[[ -1.90582925e-02  -3.05802422e-01   2.71587378e-01 ...,  -2.32252723e-01
   -3.30403605e-01   2.89468661e-01]
 [  5.85868051e-02   1.46865009e-01  -5.31210583e-04 ...,  -2.21934195e-01
    1.62758829e+00   1.17461705e-01]
 [ -5.99052480e-02   2.64854590e-01   4.71197803e-01 ...,   2.38808806e-01
   -3.10681235e-01   9.60412342e-01]
 ..., 
 [ -1.83768255e-01  -2.36150801e-01  -3.84438619e-01 ...,   9.20671209e-02
   -6.02021051e-01  -3.26381331e-01]
 [ -2.74759094e-01  -1.80666993e-01  -1.79573899e-01 ...,  -1.17012994e-01
   -1.35724872e-01  -3.56158893e-01]
 [  3.89666736e-02   8.33656433e-02  -3.97267398e-02 ...,   5.30249982e-02
    2.90805887e+00  -7.88288072e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16010298]
 [-0.94825666]
 [-1.19298038]
 [-0.76550317]
 [-0.05629954]
 [ 2.64819906]
 [-0.05123473]
 [-1.10242794]
 [-0.52829571]
 [ 1.03865041]
 [-0.0953498 ]
 [ 0.14257511]
 [-0.09862126]
 [-1.01147423]
 [-0.30091987]
 [ 0.8678701 ]
 [-0.83602344]
 [-0.79432225]
 [-0.62132221]
 [ 0.14518824]
 [-0.35179345]
 [ 4.49525421]
 [-0.94610727]
 [-1.64685619]
 [ 0.38253534]
 [-0.30374827]
 [ 4.32263588]
 [-1.92868194]]
[[ -1.90469166e-02  -3.05675620e-01   2.71903880e-01 ...,  -2.32208136e-01
   -3.29528726e-01   2.89741418e-01]
 [  5.85116624e-02   1.46428976e-01  -9.64756467e-04 ...,  -2.22065897e-01
    1.62828817e+00   1.16734134e-01]
 [ -5.99693216e-02   2.64475620e-01   4.70468547e-01 ...,   2.38694614e-01
   -3.09931762e-01   9.59447641e-01]
 ..., 
 [ -1.83841220e-01  -2.36551711e-01  -3.84715514e-01 ...,   9.19308049e-02
   -6.00543640e-01  -3.26822977e-01]
 [ -2.74829927e-01  -1.81078566e-01  -1.79820198e-01 ...,  -1.17140203e-01
   -1.35224273e-01  -3.56870375e-01]
 [  3.90239551e-02   8.37064672e-02  -3.92381535e-02 ...,   5.31305531e-02
    2.90791721e+00  -7.80894792e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.1604756 ]
 [-0.94748246]
 [-1.19147684]
 [-0.76725407]
 [-0.05718089]
 [ 2.6490456 ]
 [-0.05144197]
 [-1.10336675]
 [-0.52778735]
 [ 1.03900237]
 [-0.09606875]
 [ 0.14263061]
 [-0.0991471 ]
 [-1.01193761]
 [-0.30008754]
 [ 0.86822296]
 [-0.83569389]
 [-0.79340401]
 [-0.61995223]
 [ 0.14519587]
 [-0.35187095]
 [ 4.49466039]
 [-0.94803658]
 [-1.64666462]
 [ 0.38280017]
 [-0.30367159]
 [ 4.32329401]
 [-1.92864586]]
[[ -1.90420141e-02  -3.05674394e-01   2.71951216e-01 ...,  -2.32195764e-01
   -3.30910857e-01   2.89539363e-01]
 [  5.84864903e-02   1.46280321e-01  -1.00231300e-03 ...,  -2.22109894e-01
    1.62827082e+00   1.16569471e-01]
 [ -6.00611135e-02   2.63998842e-01   4.70101142e-01 ...,   2.38527701e-01
   -3.10072516e-01   9.58981846e-01]
 ..., 
 [ -1.83821106e-01  -2.36467675e-01  -3.84813422e-01 ...,   9.19741487e-02
   -6.00223362e-01  -3.26887616e-01]
 [ -2.74780465e-01  -1.80824196e-01  -1.79551130e-01 ...,  -1.17047945e-01
   -1.36127329e-01  -3.56561415e-01]
 [  3.88794587e-02   8.28631729e-02  -3.99535955e-02 ...,   5.28639238e-02
    2.90844084e+00  -7.93687219e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16584432]
 [-0.95284945]
 [-1.19898888]
 [-0.77007225]
 [-0.0609964 ]
 [ 2.64569097]
 [-0.05576152]
 [-1.10474671]
 [-0.53466506]
 [ 1.03439954]
 [-0.09976142]
 [ 0.13758077]
 [-0.10484767]
 [-1.01575667]
 [-0.30666367]
 [ 0.86123862]
 [-0.84192394]
 [-0.80035484]
 [-0.6269702 ]
 [ 0.14020499]
 [-0.35730432]
 [ 4.49380631]
 [-0.94955114]
 [-1.65023067]
 [ 0.37830466]
 [-0.30906118]
 [ 4.31484321]
 [-1.9312171 ]]
[[ -1.87507735e-02  -3.03924338e-01   2.73693271e-01 ...,  -2.31631532e-01
   -3.34351753e-01   2.92420105e-01]
 [  5.84486174e-02   1.46062794e-01  -1.26030772e-03 ...,  -2.22176088e-01
    1.62860766e+00   1.16256882e-01]
 [ -5.96649000e-02   2.66333418e-01   4.72464060e-01 ...,   2.39280107e-01
   -3.15403333e-01   9.62194090e-01]
 ..., 
 [ -1.83749835e-01  -2.36094208e-01  -3.84304012e-01 ...,   9.21084939e-02
   -6.01942396e-01  -3.26348651e-01]
 [ -2.74599876e-01  -1.79743055e-01  -1.78398553e-01 ...,  -1.16700856e-01
   -1.38258635e-01  -3.55124793e-01]
 [  3.88977046e-02   8.29711696e-02  -3.97989703e-02 ...,   5.28945544e-02
    2.90847000e+00  -7.92688215e-02]]
Progress: 81.1% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.16276063]
 [-0.95045368]
 [-1.19548889]
 [-0.76786242]
 [-0.05919091]
 [ 2.64749267]
 [-0.05330988]
 [-1.10353329]
 [-0.53138236]
 [ 1.03725615]
 [-0.09749199]
 [ 0.14022877]
 [-0.10183418]
 [-1.01306235]
 [-0.30398286]
 [ 0.86447763]
 [-0.83884532]
 [-0.7967037 ]
 [-0.62398174]
 [ 0.14246688]
 [-0.35416785]
 [ 4.49472466]
 [-0.94751953]
 [-1.6485291 ]
 [ 0.38077434]
 [-0.30655783]
 [ 4.32003348]
 [-1.92909852]]
[[ -1.88432351e-02  -3.04425352e-01   2.73402716e-01 ...,  -2.31808221e-01
   -3.34750895e-01   2.91016068e-01]
 [  5.84774785e-02   1.46251757e-01  -1.07208074e-03 ...,  -2.22131161e-01
    1.62878097e+00   1.16347720e-01]
 [ -5.98222422e-02   2.65287804e-01   4.71404919e-01 ...,   2.38990088e-01
   -3.14780870e-01   9.60065027e-01]
 ..., 
 [ -1.83854722e-01  -2.36656735e-01  -3.84779438e-01 ...,   9.19176413e-02
   -6.00142905e-01  -3.27204724e-01]
 [ -2.74577734e-01  -1.79655447e-01  -1.78525687e-01 ...,  -1.16660925e-01
   -1.39163531e-01  -3.55295932e-01]
 [  3.88292505e-02   8.26114287e-02  -4.02420099e-02 ...,   5.27688605e-02
    2.90893216e+00  -8.00984992e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16162828]
 [-0.9489391 ]
 [-1.19526239]
 [-0.76649062]
 [-0.05770359]
 [ 2.64915166]
 [-0.0514845 ]
 [-1.10208964]
 [-0.53030493]
 [ 1.0375616 ]
 [-0.09534865]
 [ 0.14169858]
 [-0.1002907 ]
 [-1.01152761]
 [-0.30226135]
 [ 0.86568304]
 [-0.83761649]
 [-0.79670914]
 [-0.62291719]
 [ 0.14358982]
 [-0.35301551]
 [ 4.49406047]
 [-0.94638438]
 [-1.64749097]
 [ 0.38235592]
 [-0.30580977]
 [ 4.32244211]
 [-1.92877897]]
[[ -1.89731374e-02  -3.05131162e-01   2.72724906e-01 ...,  -2.32032189e-01
   -3.32976680e-01   2.89598617e-01]
 [  5.83730600e-02   1.45636179e-01  -1.71958575e-03 ...,  -2.22324764e-01
    1.62965934e+00   1.15166229e-01]
 [ -5.97894921e-02   2.65488997e-01   4.71483743e-01 ...,   2.39050792e-01
   -3.15174548e-01   9.58940042e-01]
 ..., 
 [ -1.83824972e-01  -2.36460248e-01  -3.84499181e-01 ...,   9.19702919e-02
   -6.00281492e-01  -3.26755414e-01]
 [ -2.74583411e-01  -1.79688716e-01  -1.78528835e-01 ...,  -1.16669029e-01
   -1.38563296e-01  -3.55512202e-01]
 [  3.87584242e-02   8.22262838e-02  -4.05672614e-02 ...,   5.26496654e-02
    2.90913228e+00  -8.11509095e-02]]
Progress: 81.1% ... Training loss: 0.060 ... Validation loss: 0.139[[-0.16078242]
 [-0.9482943 ]
 [-1.19397236]
 [-0.76610799]
 [-0.05728153]
 [ 2.65108059]
 [-0.05052374]
 [-1.10270031]
 [-0.52946297]
 [ 1.03756435]
 [-0.093966  ]
 [ 0.14211549]
 [-0.09986211]
 [-1.01034011]
 [-0.30134272]
 [ 0.86575894]
 [-0.83642481]
 [-0.79559982]
 [-0.62220225]
 [ 0.14374933]
 [-0.35283255]
 [ 4.4944804 ]
 [-0.94557168]
 [-1.64887162]
 [ 0.3833922 ]
 [-0.3051873 ]
 [ 4.32363496]
 [-1.92763171]]
[[ -1.89624389e-02  -3.05067112e-01   2.72426919e-01 ...,  -2.32004794e-01
   -3.33478143e-01   2.89135213e-01]
 [  5.83498620e-02   1.45481315e-01  -1.90086103e-03 ...,  -2.22370587e-01
    1.62994766e+00   1.14650247e-01]
 [ -5.99622891e-02   2.64546179e-01   4.70392635e-01 ...,   2.38746787e-01
   -3.13599616e-01   9.56363898e-01]
 ..., 
 [ -1.83811541e-01  -2.36391144e-01  -3.84307275e-01 ...,   9.19960763e-02
   -5.99568909e-01  -3.26698709e-01]
 [ -2.74524380e-01  -1.79357080e-01  -1.78200124e-01 ...,  -1.16557596e-01
   -1.38817556e-01  -3.55309931e-01]
 [  3.86259639e-02   8.14729640e-02  -4.13844979e-02 ...,   5.23947705e-02
    2.90934320e+00  -8.24145114e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16186032]
 [-0.94977964]
 [-1.19569768]
 [-0.76599284]
 [-0.05765305]
 [ 2.64920754]
 [-0.05212272]
 [-1.10134702]
 [-0.531344  ]
 [ 1.0361268 ]
 [-0.09572879]
 [ 0.14171183]
 [-0.10095086]
 [-1.01310268]
 [-0.30267671]
 [ 0.86530151]
 [-0.83772609]
 [-0.79799915]
 [-0.62364929]
 [ 0.1432823 ]
 [-0.35341068]
 [ 4.49433834]
 [-0.94729498]
 [-1.64804772]
 [ 0.38191395]
 [-0.30602901]
 [ 4.32145986]
 [-1.92968106]]
[[ -1.89825564e-02  -3.05212459e-01   2.72349954e-01 ...,  -2.32044694e-01
   -3.33618526e-01   2.89526110e-01]
 [  5.84821717e-02   1.46243841e-01  -9.55110822e-04 ...,  -2.22124587e-01
    1.62957661e+00   1.15750029e-01]
 [ -5.96235220e-02   2.66509560e-01   4.72737062e-01 ...,   2.39377590e-01
   -3.13236667e-01   9.59906870e-01]
 ..., 
 [ -1.83869225e-01  -2.36721548e-01  -3.84427929e-01 ...,   9.18887852e-02
   -5.98835654e-01  -3.27131007e-01]
 [ -2.74502650e-01  -1.79245902e-01  -1.78315952e-01 ...,  -1.16515593e-01
   -1.38434158e-01  -3.55279065e-01]
 [  3.85838571e-02   8.12253586e-02  -4.15732576e-02 ...,   5.23065204e-02
    2.90927274e+00  -8.22305071e-02]]
Progress: 81.1% ... Training loss: 0.060 ... Validation loss: 0.139[[-0.16293582]
 [-0.9512322 ]
 [-1.19530027]
 [-0.76825977]
 [-0.05904225]
 [ 2.64801512]
 [-0.0537888 ]
 [-1.102241  ]
 [-0.53235193]
 [ 1.03636727]
 [-0.0965401 ]
 [ 0.14080019]
 [-0.10288798]
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 [-0.30381569]
 [ 0.86512467]
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 [ 0.14184424]
 [-0.35431415]
 [ 4.49493501]
 [-0.94976947]
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 [ 0.38080852]
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 [ 4.31984129]
 [-1.93118166]]
[[ -1.89765082e-02  -3.05219254e-01   2.71968789e-01 ...,  -2.32039132e-01
   -3.34792462e-01   2.90157865e-01]
 [  5.85218515e-02   1.46453784e-01  -6.67603393e-04 ...,  -2.22053254e-01
    1.62930349e+00   1.16198109e-01]
 [ -5.95395988e-02   2.67076435e-01   4.73597882e-01 ...,   2.39537406e-01
   -3.14081486e-01   9.61892204e-01]
 ..., 
 [ -1.83888391e-01  -2.36843471e-01  -3.84565172e-01 ...,   9.18553210e-02
   -5.98543978e-01  -3.27240507e-01]
 [ -2.74499033e-01  -1.79248229e-01  -1.78492864e-01 ...,  -1.16509965e-01
   -1.38891027e-01  -3.55216602e-01]
 [  3.86180722e-02   8.14134360e-02  -4.14091163e-02 ...,   5.23703093e-02
    2.90923242e+00  -8.18818250e-02]]
Progress: 81.1% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16547668]
 [-0.95321645]
 [-1.19709336]
 [-0.77000399]
 [-0.06068227]
 [ 2.64665128]
 [-0.05601057]
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 [-0.53380645]
 [ 1.0348029 ]
 [-0.09878109]
 [ 0.13886419]
 [-0.10529139]
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 [-0.30599055]
 [ 0.8636019 ]
 [-0.84132662]
 [-0.80031993]
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 [ 0.14000051]
 [-0.35599773]
 [ 4.49453017]
 [-0.95276286]
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 [ 0.37908236]
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 [ 4.31580428]
 [-1.93241378]]
[[ -1.88857154e-02  -3.04691132e-01   2.72612067e-01 ...,  -2.31869186e-01
   -3.34713793e-01   2.90811484e-01]
 [  5.85277383e-02   1.46478194e-01  -6.55173745e-04 ...,  -2.22042604e-01
    1.62893850e+00   1.16287424e-01]
 [ -5.95453576e-02   2.67046131e-01   4.73838049e-01 ...,   2.39534486e-01
   -3.13552627e-01   9.62072201e-01]
 ..., 
 [ -1.83866518e-01  -2.36713277e-01  -3.84653310e-01 ...,   9.19022732e-02
   -5.99095895e-01  -3.27025197e-01]
 [ -2.74453653e-01  -1.79041767e-01  -1.78253767e-01 ...,  -1.16441971e-01
   -1.40478745e-01  -3.55105129e-01]
 [  3.87216387e-02   8.20087065e-02  -4.06822025e-02 ...,   5.25688445e-02
    2.90916958e+00  -8.10368460e-02]]
Progress: 81.1% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.16260438]
 [-0.95187376]
 [-1.19551373]
 [-0.76760505]
 [-0.05874811]
 [ 2.64874922]
 [-0.05382349]
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 [ 1.03607761]
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 [ 0.14071602]
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 [-1.01430158]
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 [ 0.86567936]
 [-0.83878093]
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 [ 0.14198752]
 [-0.35442455]
 [ 4.49451553]
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 [-1.64892895]
 [ 0.38095429]
 [-0.30705435]
 [ 4.31899731]
 [-1.93050135]]
[[ -1.90107992e-02  -3.05255479e-01   2.72062836e-01 ...,  -2.32081311e-01
   -3.31401975e-01   2.89896180e-01]
 [  5.85545251e-02   1.46627920e-01  -5.28829063e-04 ...,  -2.21994819e-01
    1.62867770e+00   1.16412265e-01]
 [ -5.95961463e-02   2.66827231e-01   4.72910686e-01 ...,   2.39463756e-01
   -3.11806252e-01   9.60251018e-01]
 ..., 
 [ -1.83853185e-01  -2.36610264e-01  -3.84624202e-01 ...,   9.19372605e-02
   -5.99276447e-01  -3.27306312e-01]
 [ -2.74465821e-01  -1.79105516e-01  -1.78352422e-01 ...,  -1.16483332e-01
   -1.39716951e-01  -3.55454178e-01]
 [  3.86781638e-02   8.17612133e-02  -4.10293591e-02 ...,   5.24922322e-02
    2.90924221e+00  -8.12831467e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16643726]
 [-0.95533476]
 [-1.19888649]
 [-0.77033993]
 [-0.06098605]
 [ 2.646278  ]
 [-0.05677056]
 [-1.10488858]
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 [ 1.03392166]
 [-0.09984384]
 [ 0.13757139]
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 [-1.01592393]
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 [ 0.86096824]
 [-0.84259474]
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 [ 0.13885075]
 [-0.3579205 ]
 [ 4.49199311]
 [-0.95089711]
 [-1.65217064]
 [ 0.37785618]
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 [ 4.31212333]
 [-1.93167976]]
[[ -1.88005695e-02  -3.03978868e-01   2.73323932e-01 ...,  -2.31689080e-01
   -3.32404517e-01   2.91773742e-01]
 [  5.85114411e-02   1.46374761e-01  -8.33003569e-04 ...,  -2.22074081e-01
    1.62942234e+00   1.15935770e-01]
 [ -5.95191118e-02   2.67276741e-01   4.72951302e-01 ...,   2.39622188e-01
   -3.13226372e-01   9.60578111e-01]
 ..., 
 [ -1.83837607e-01  -2.36519390e-01  -3.84704339e-01 ...,   9.19698712e-02
   -5.99097889e-01  -3.27103141e-01]
 [ -2.74390382e-01  -1.78670387e-01  -1.77913889e-01 ...,  -1.16363727e-01
   -1.39896793e-01  -3.55183214e-01]
 [  3.87069847e-02   8.19360646e-02  -4.08388731e-02 ...,   5.25491292e-02
    2.90917066e+00  -8.08310987e-02]]
Progress: 81.2% ... Training loss: 0.065 ... Validation loss: 0.137[[-0.15770888]
 [-0.94891916]
 [-1.19234119]
 [-0.76297663]
 [-0.05408894]
 [ 2.6500204 ]
 [-0.04983254]
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 [ 1.03844718]
 [-0.09295124]
 [ 0.14539214]
 [-0.09833509]
 [-1.01166116]
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 [ 0.87089245]
 [-0.83430122]
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 [ 0.14646231]
 [-0.34988099]
 [ 4.49272135]
 [-0.94565376]
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 [ 0.3840648 ]
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 [ 4.32571318]
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[[ -1.91657930e-02  -3.05854848e-01   2.71554802e-01 ...,  -2.32342979e-01
   -3.27880402e-01   2.88512373e-01]
 [  5.85025329e-02   1.46368940e-01  -1.02730258e-03 ...,  -2.22082983e-01
    1.63003444e+00   1.15840993e-01]
 [ -5.94296482e-02   2.67733578e-01   4.73369950e-01 ...,   2.39767552e-01
   -3.14213174e-01   9.59338787e-01]
 ..., 
 [ -1.83930382e-01  -2.37036451e-01  -3.85110140e-01 ...,   9.18026824e-02
   -5.97902041e-01  -3.27821638e-01]
 [ -2.74411884e-01  -1.78781613e-01  -1.77975430e-01 ...,  -1.16400444e-01
   -1.38896653e-01  -3.55278298e-01]
 [  3.85034013e-02   8.08021731e-02  -4.19789600e-02 ...,   5.21772588e-02
    2.90966127e+00  -8.27070432e-02]]
Progress: 81.2% ... Training loss: 0.063 ... Validation loss: 0.147[[-0.16303335]
 [-0.95312428]
 [-1.19627602]
 [-0.76766949]
 [-0.05800772]
 [ 2.64839548]
 [-0.05398228]
 [-1.10196802]
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 [ 1.03503316]
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 [ 0.14087214]
 [-0.10253466]
 [-1.01502991]
 [-0.30442493]
 [ 0.8656748 ]
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 [ 0.14219071]
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 [ 4.49165056]
 [-0.94978564]
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 [ 0.38071789]
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 [ 4.31798755]
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[[ -1.89405455e-02  -3.04545099e-01   2.72663985e-01 ...,  -2.31926230e-01
   -3.29960590e-01   2.90318781e-01]
 [  5.85235508e-02   1.46490739e-01  -9.46193276e-04 ...,  -2.22047392e-01
    1.62986355e+00   1.16007501e-01]
 [ -5.94297778e-02   2.67717207e-01   4.73595757e-01 ...,   2.39765146e-01
   -3.15193264e-01   9.60243295e-01]
 ..., 
 [ -1.83832843e-01  -2.36471413e-01  -3.84344634e-01 ...,   9.19879823e-02
   -5.99099297e-01  -3.26835288e-01]
 [ -2.74483471e-01  -1.79199397e-01  -1.78499718e-01 ...,  -1.16536424e-01
   -1.38655074e-01  -3.56317416e-01]
 [  3.85085392e-02   8.08340633e-02  -4.20044819e-02 ...,   5.21850448e-02
    2.90985706e+00  -8.26169591e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1632911 ]
 [-0.95309196]
 [-1.1975557 ]
 [-0.76735296]
 [-0.05806384]
 [ 2.64858678]
 [-0.05402066]
 [-1.10149918]
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 [ 1.03478196]
 [-0.09754284]
 [ 0.14096311]
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 [-1.01523464]
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 [ 0.86551278]
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 [ 0.14215979]
 [-0.35424538]
 [ 4.4908772 ]
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 [ 0.38098953]
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 [ 4.31743223]
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[[ -1.88385208e-02  -3.03907454e-01   2.73320480e-01 ...,  -2.31727486e-01
   -3.28992767e-01   2.91011179e-01]
 [  5.85449776e-02   1.46597547e-01  -8.35894721e-04 ...,  -2.22009090e-01
    1.62975768e+00   1.16091544e-01]
 [ -5.93802569e-02   2.68068051e-01   4.73875518e-01 ...,   2.39862212e-01
   -3.14031012e-01   9.60942464e-01]
 ..., 
 [ -1.83812124e-01  -2.36344587e-01  -3.84338020e-01 ...,   9.20263709e-02
   -5.98621444e-01  -3.26824340e-01]
 [ -2.74413894e-01  -1.78769597e-01  -1.77945404e-01 ...,  -1.16413061e-01
   -1.38633126e-01  -3.55715737e-01]
 [  3.84729898e-02   8.06355273e-02  -4.19570618e-02 ...,   5.21209255e-02
    2.90988564e+00  -8.27506378e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1581863 ]
 [-0.94823858]
 [-1.19303116]
 [-0.76357139]
 [-0.0544734 ]
 [ 2.65292094]
 [-0.04903284]
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 [ 0.14581343]
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 [ 0.14673256]
 [-0.34918024]
 [ 4.49238592]
 [-0.9468387 ]
 [-1.64563833]
 [ 0.38584295]
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 [ 4.32657438]
 [-1.927913  ]]
[[ -1.91831586e-02  -3.05872583e-01   2.71251808e-01 ...,  -2.32355347e-01
   -3.25961190e-01   2.88223266e-01]
 [  5.84639250e-02   1.46167569e-01  -1.10707190e-03 ...,  -2.22159486e-01
    1.63026990e+00   1.15439532e-01]
 [ -5.97067136e-02   2.66188651e-01   4.71983379e-01 ...,   2.39265245e-01
   -3.09937738e-01   9.57192215e-01]
 ..., 
 [ -1.83789986e-01  -2.36207646e-01  -3.84477124e-01 ...,   9.20686557e-02
   -5.99377968e-01  -3.26824975e-01]
 [ -2.74531252e-01  -1.79450893e-01  -1.78512480e-01 ...,  -1.16630738e-01
   -1.37507164e-01  -3.56511778e-01]
 [  3.84626457e-02   8.05657248e-02  -4.20366114e-02 ...,   5.21023878e-02
    2.91011127e+00  -8.30874259e-02]]
Progress: 81.2% ... Training loss: 0.063 ... Validation loss: 0.146[[-0.16551619]
 [-0.95539545]
 [-1.1986301 ]
 [-0.77039615]
 [-0.06058828]
 [ 2.64846655]
 [-0.05533369]
 [-1.10447635]
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 [ 1.03376535]
 [-0.09945997]
 [ 0.13929252]
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 [ 0.86356102]
 [-0.84240113]
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 [ 0.14009102]
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 [ 4.49191392]
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 [-1.65106558]
 [ 0.37986184]
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 [ 4.31427166]
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[[ -1.90682910e-02  -3.05137927e-01   2.72070991e-01 ...,  -2.32129666e-01
   -3.27417687e-01   2.89732310e-01]
 [  5.84824488e-02   1.46217426e-01  -1.11171568e-03 ...,  -2.22121500e-01
    1.63070993e+00   1.15668042e-01]
 [ -5.94161375e-02   2.67744568e-01   4.74061593e-01 ...,   2.39817679e-01
   -3.13046850e-01   9.60733391e-01]
 ..., 
 [ -1.83789395e-01  -2.36176949e-01  -3.84416487e-01 ...,   9.20733835e-02
   -5.98916105e-01  -3.27129252e-01]
 [ -2.74522147e-01  -1.79423122e-01  -1.78602335e-01 ...,  -1.16611771e-01
   -1.37677203e-01  -3.56629719e-01]
 [  3.86447548e-02   8.16601110e-02  -4.08430442e-02 ...,   5.24475875e-02
    2.90980762e+00  -8.17907455e-02]]
Progress: 81.2% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16456511]
 [-0.95498609]
 [-1.19918466]
 [-0.76945669]
 [-0.05954748]
 [ 2.64833277]
 [-0.0547102 ]
 [-1.10271995]
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 [ 0.13993781]
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 [-1.01547249]
 [-0.30565846]
 [ 0.86373346]
 [-0.84184087]
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 [-0.62641656]
 [ 0.14070779]
 [-0.35538394]
 [ 4.49154933]
 [-0.94977417]
 [-1.64913541]
 [ 0.38003109]
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 [ 4.31537698]
 [-1.93178847]]
[[ -1.90140187e-02  -3.04846108e-01   2.72399895e-01 ...,  -2.32022379e-01
   -3.28433352e-01   2.90657695e-01]
 [  5.84989446e-02   1.46303252e-01  -9.91963440e-04 ...,  -2.22092859e-01
    1.63057451e+00   1.15784611e-01]
 [ -5.92934114e-02   2.68480263e-01   4.74654140e-01 ...,   2.40051534e-01
   -3.12780850e-01   9.60841788e-01]
 ..., 
 [ -1.83784604e-01  -2.36162497e-01  -3.84464664e-01 ...,   9.20846493e-02
   -5.98434832e-01  -3.27250328e-01]
 [ -2.74492923e-01  -1.79268574e-01  -1.78249991e-01 ...,  -1.16547907e-01
   -1.38285800e-01  -3.56285717e-01]
 [  3.86338362e-02   8.16229356e-02  -4.10317821e-02 ...,   5.24336134e-02
    2.90980277e+00  -8.17672515e-02]]
Progress: 81.2% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.15872518]
 [-0.95005276]
 [-1.19506126]
 [-0.76424604]
 [-0.05476568]
 [ 2.65099775]
 [-0.04951432]
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 [ 1.03765056]
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 [ 0.14493458]
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 [-1.01148242]
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 [ 0.86957295]
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 [-0.62216148]
 [ 0.14566197]
 [-0.35057114]
 [ 4.49353165]
 [-0.94510901]
 [-1.64396983]
 [ 0.3844288 ]
 [-0.30395811]
 [ 4.3250192 ]
 [-1.92926064]]
[[ -1.92134277e-02  -3.05996378e-01   2.71087006e-01 ...,  -2.32379466e-01
   -3.25702753e-01   2.89296137e-01]
 [  5.84969328e-02   1.46296679e-01  -1.11276422e-03 ...,  -2.22101971e-01
    1.63047476e+00   1.15653425e-01]
 [ -5.93756673e-02   2.67941838e-01   4.73697160e-01 ...,   2.39916259e-01
   -3.11178176e-01   9.58426917e-01]
 ..., 
 [ -1.83833730e-01  -2.36446432e-01  -3.84921652e-01 ...,   9.19917849e-02
   -5.97277069e-01  -3.28001965e-01]
 [ -2.74604673e-01  -1.79929421e-01  -1.78940550e-01 ...,  -1.16748928e-01
   -1.37369417e-01  -3.56951956e-01]
 [  3.86170359e-02   8.15137750e-02  -4.11175833e-02 ...,   5.24023664e-02
    2.90983435e+00  -8.17135842e-02]]
Progress: 81.2% ... Training loss: 0.062 ... Validation loss: 0.147[[-0.16232385]
 [-0.9525797 ]
 [-1.19806816]
 [-0.76768955]
 [-0.05801462]
 [ 2.6509256 ]
 [-0.05234994]
 [-1.10207055]
 [-0.53196137]
 [ 1.03540295]
 [-0.09686161]
 [ 0.14194141]
 [-0.10222544]
 [-1.01283204]
 [-0.30362099]
 [ 0.86577439]
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 [ 0.142566  ]
 [-0.35370538]
 [ 4.49269022]
 [-0.94785068]
 [-1.64908591]
 [ 0.38249225]
 [-0.30675866]
 [ 4.31932813]
 [-1.93054804]]
[[ -1.90668121e-02  -3.05141048e-01   2.71997858e-01 ...,  -2.32102346e-01
   -3.27183745e-01   2.90663550e-01]
 [  5.85257772e-02   1.46441790e-01  -1.00367740e-03 ...,  -2.22059020e-01
    1.63037687e+00   1.15775136e-01]
 [ -5.95434817e-02   2.67110699e-01   4.73202063e-01 ...,   2.39626479e-01
   -3.11368997e-01   9.58582505e-01]
 ..., 
 [ -1.83776800e-01  -2.36170464e-01  -3.84774466e-01 ...,   9.20995862e-02
   -5.97742624e-01  -3.27992150e-01]
 [ -2.74545516e-01  -1.79556857e-01  -1.78623541e-01 ...,  -1.16632536e-01
   -1.38030223e-01  -3.56455339e-01]
 [  3.85943471e-02   8.13880733e-02  -4.11561149e-02 ...,   5.23670232e-02
    2.91004382e+00  -8.18406250e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.15962429]
 [-0.95028864]
 [-1.19679812]
 [-0.76534351]
 [-0.05589583]
 [ 2.65214465]
 [-0.05078114]
 [-1.10002917]
 [-0.53009396]
 [ 1.03580688]
 [-0.09530435]
 [ 0.14395401]
 [-0.09976371]
 [-1.0120352 ]
 [-0.30101238]
 [ 0.86832156]
 [-0.83748932]
 [-0.79763843]
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 [ 0.14500513]
 [-0.35119159]
 [ 4.49351369]
 [-0.94660971]
 [-1.64655762]
 [ 0.3835566 ]
 [-0.30432817]
 [ 4.32368442]
 [-1.93013674]]
[[ -1.92731104e-02  -3.06360161e-01   2.70799964e-01 ...,  -2.32497533e-01
   -3.25892883e-01   2.89019680e-01]
 [  5.85352590e-02   1.46497371e-01  -9.87896267e-04 ...,  -2.22041764e-01
    1.63036781e+00   1.15801507e-01]
 [ -5.95264345e-02   2.67281287e-01   4.73399809e-01 ...,   2.39690099e-01
   -3.09540979e-01   9.58697293e-01]
 ..., 
 [ -1.83792644e-01  -2.36267391e-01  -3.84692290e-01 ...,   9.20696704e-02
   -5.97678307e-01  -3.28015547e-01]
 [ -2.74494965e-01  -1.79267672e-01  -1.78417162e-01 ...,  -1.16540422e-01
   -1.38580948e-01  -3.55999380e-01]
 [  3.84775329e-02   8.06664148e-02  -4.19002660e-02 ...,   5.21505409e-02
    2.91023131e+00  -8.25342097e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.143[[-0.16632111]
 [-0.95665932]
 [-1.20316119]
 [-0.77116068]
 [-0.06244616]
 [ 2.65000659]
 [-0.05637022]
 [-1.10614855]
 [-0.53614878]
 [ 1.03106322]
 [-0.1014145 ]
 [ 0.13757842]
 [-0.10658568]
 [-1.01503253]
 [-0.30780492]
 [ 0.85980795]
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 [ 0.13947587]
 [-0.35783219]
 [ 4.49285059]
 [-0.95050825]
 [-1.65458709]
 [ 0.37846375]
 [-0.31047161]
 [ 4.31176177]
 [-1.93237526]]
[[ -1.90854217e-02  -3.05284400e-01   2.71813310e-01 ...,  -2.32142948e-01
   -3.27828038e-01   2.90636156e-01]
 [  5.86125975e-02   1.46933945e-01  -7.47045434e-04 ...,  -2.21890318e-01
    1.62982897e+00   1.16414195e-01]
 [ -5.95020713e-02   2.67415914e-01   4.73816666e-01 ...,   2.39751829e-01
   -3.09829727e-01   9.59834225e-01]
 ..., 
 [ -1.83742540e-01  -2.35992769e-01  -3.84705229e-01 ...,   9.21646606e-02
   -5.98460614e-01  -3.27726391e-01]
 [ -2.74373542e-01  -1.78558815e-01  -1.77656690e-01 ...,  -1.16310923e-01
   -1.39414525e-01  -3.55145892e-01]
 [  3.85366082e-02   8.10418136e-02  -4.15908784e-02 ...,   5.22678061e-02
    2.91025604e+00  -8.23169647e-02]]
Progress: 81.2% ... Training loss: 0.065 ... Validation loss: 0.138[[-0.15869782]
 [-0.94982487]
 [-1.19770269]
 [-0.76322921]
 [-0.05589496]
 [ 2.65371856]
 [-0.04883476]
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 [ 1.03484079]
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 [ 0.14451287]
 [-0.09834725]
 [-1.00887435]
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 [ 0.86801513]
 [-0.83764539]
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 [ 0.14631055]
 [-0.35105473]
 [ 4.49567647]
 [-0.94415208]
 [-1.64818867]
 [ 0.38426714]
 [-0.30343772]
 [ 4.32440263]
 [-1.92770186]]
[[ -1.94884696e-02  -3.07515238e-01   2.69798961e-01 ...,  -2.32851581e-01
   -3.21743370e-01   2.86731083e-01]
 [  5.85951260e-02   1.46815594e-01  -8.90205091e-04 ...,  -2.21912580e-01
    1.63060633e+00   1.16178273e-01]
 [ -5.96397780e-02   2.66532048e-01   4.72362991e-01 ...,   2.39517755e-01
   -3.07471063e-01   9.56575368e-01]
 ..., 
 [ -1.83936677e-01  -2.37042128e-01  -3.85691074e-01 ...,   9.18054664e-02
   -5.95826718e-01  -3.29148252e-01]
 [ -2.74541158e-01  -1.79528940e-01  -1.78530526e-01 ...,  -1.16599943e-01
   -1.37136705e-01  -3.56793165e-01]
 [  3.85291279e-02   8.10238150e-02  -4.13460160e-02 ...,   5.22603920e-02
    2.91022849e+00  -8.23107516e-02]]
Progress: 81.2% ... Training loss: 0.063 ... Validation loss: 0.148[[-0.16083907]
 [-0.95097658]
 [-1.19789767]
 [-0.76594728]
 [-0.05764698]
 [ 2.65180531]
 [-0.05055345]
 [-1.10194288]
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 [ 1.03532884]
 [-0.09573212]
 [ 0.14259074]
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 [-1.01080813]
 [-0.30237453]
 [ 0.86590624]
 [-0.83905017]
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 [-0.62400125]
 [ 0.14406371]
 [-0.3526052 ]
 [ 4.49579646]
 [-0.94668438]
 [-1.64979839]
 [ 0.38293794]
 [-0.30502244]
 [ 4.32134233]
 [-1.92885238]]
[[ -1.93450863e-02  -3.06717241e-01   2.70427954e-01 ...,  -2.32584507e-01
   -3.24048063e-01   2.88120039e-01]
 [  5.85493769e-02   1.46534780e-01  -9.70957237e-04 ...,  -2.21992947e-01
    1.63041991e+00   1.15979214e-01]
 [ -5.96386973e-02   2.66581768e-01   4.72294923e-01 ...,   2.39521187e-01
   -3.08438879e-01   9.57629369e-01]
 ..., 
 [ -1.83931241e-01  -2.37041643e-01  -3.85682027e-01 ...,   9.18148442e-02
   -5.96337326e-01  -3.29100928e-01]
 [ -2.74493029e-01  -1.79260101e-01  -1.78253149e-01 ...,  -1.16517373e-01
   -1.38469857e-01  -3.56486263e-01]
 [  3.85861576e-02   8.13452353e-02  -4.13101031e-02 ...,   5.23660880e-02
    2.91004398e+00  -8.17453713e-02]]
Progress: 81.2% ... Training loss: 0.061 ... Validation loss: 0.142[[-0.16181383]
 [-0.95210751]
 [-1.19917961]
 [-0.76664974]
 [-0.05871777]
 [ 2.65063005]
 [-0.05162038]
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 [-0.53149803]
 [ 1.03488824]
 [-0.09635555]
 [ 0.14128934]
 [-0.10262651]
 [-1.01168118]
 [-0.30368346]
 [ 0.86432154]
 [-0.84029033]
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 [ 0.14279282]
 [-0.35340925]
 [ 4.49552492]
 [-0.9467412 ]
 [-1.65052192]
 [ 0.38199564]
 [-0.30662537]
 [ 4.31961749]
 [-1.92975788]]
[[ -1.92447902e-02  -3.06116814e-01   2.71050619e-01 ...,  -2.32411174e-01
   -3.25459548e-01   2.89200275e-01]
 [  5.85493769e-02   1.46534780e-01  -9.70957237e-04 ...,  -2.21992947e-01
    1.63041991e+00   1.15979214e-01]
 [ -5.95626153e-02   2.67040957e-01   4.72555410e-01 ...,   2.39648273e-01
   -3.08516429e-01   9.58838359e-01]
 ..., 
 [ -1.83901066e-01  -2.36840884e-01  -3.85481749e-01 ...,   9.18741727e-02
   -5.96633122e-01  -3.28785682e-01]
 [ -2.74445523e-01  -1.78996255e-01  -1.77843077e-01 ...,  -1.16455289e-01
   -1.39454495e-01  -3.56002147e-01]
 [  3.86404141e-02   8.16432092e-02  -4.09751605e-02 ...,   5.24588597e-02
    2.90991185e+00  -8.10620556e-02]]
Progress: 81.2% ... Training loss: 0.060 ... Validation loss: 0.140[[-0.1613517 ]
 [-0.95168498]
 [-1.19768715]
 [-0.76645657]
 [-0.05878706]
 [ 2.65146529]
 [-0.05120632]
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 [ 1.03518562]
 [-0.09609252]
 [ 0.14119775]
 [-0.10271191]
 [-1.01116597]
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 [ 0.86465641]
 [-0.83966301]
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 [ 0.14276441]
 [-0.35349508]
 [ 4.49486832]
 [-0.94654853]
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 [ 0.38244145]
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 [ 4.32022703]
 [-1.92855665]]
[[ -1.92002951e-02  -3.05895679e-01   2.71380555e-01 ...,  -2.32329973e-01
   -3.26528178e-01   2.89470687e-01]
 [  5.85509486e-02   1.46543390e-01  -9.61654697e-04 ...,  -2.21989954e-01
    1.63041333e+00   1.15997148e-01]
 [ -5.97108049e-02   2.66186569e-01   4.71819014e-01 ...,   2.39407008e-01
   -3.06184303e-01   9.57366865e-01]
 ..., 
 [ -1.83898515e-01  -2.36836375e-01  -3.85364643e-01 ...,   9.18724572e-02
   -5.96190631e-01  -3.28919778e-01]
 [ -2.74327342e-01  -1.78311751e-01  -1.77160453e-01 ...,  -1.16228286e-01
   -1.40522337e-01  -3.55347026e-01]
 [  3.85627216e-02   8.11431612e-02  -4.14558874e-02 ...,   5.23066457e-02
    2.91010885e+00  -8.15463860e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15881577]
 [-0.9498533 ]
 [-1.19492199]
 [-0.76538037]
 [-0.05691661]
 [ 2.65249041]
 [-0.04961631]
 [-1.10166444]
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 [ 1.03731697]
 [-0.09352164]
 [ 0.14329678]
 [-0.10105659]
 [-1.00963549]
 [-0.30100818]
 [ 0.86791202]
 [-0.83711256]
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 [ 0.14464998]
 [-0.35052835]
 [ 4.49611487]
 [-0.94522939]
 [-1.64856331]
 [ 0.38445228]
 [-0.304418  ]
 [ 4.32273012]
 [-1.92774047]]
[[ -1.93129662e-02  -3.06582860e-01   2.70299938e-01 ...,  -2.32547578e-01
   -3.23980806e-01   2.88984015e-01]
 [  5.85244042e-02   1.46387753e-01  -1.16698530e-03 ...,  -2.22034865e-01
    1.63069510e+00   1.15697363e-01]
 [ -5.97950044e-02   2.65672248e-01   4.71228499e-01 ...,   2.39234506e-01
   -3.02057887e-01   9.55899001e-01]
 ..., 
 [ -1.83893280e-01  -2.36798063e-01  -3.85296135e-01 ...,   9.18839397e-02
   -5.95849221e-01  -3.28787860e-01]
 [ -2.74336094e-01  -1.78410124e-01  -1.77188017e-01 ...,  -1.16249393e-01
   -1.40575793e-01  -3.55387700e-01]
 [  3.86130069e-02   8.14393565e-02  -4.13866115e-02 ...,   5.23871799e-02
    2.90991977e+00  -8.13295034e-02]]
Progress: 81.3% ... Training loss: 0.062 ... Validation loss: 0.145[[-0.16371615]
 [-0.95363918]
 [-1.19921658]
 [-0.76847352]
 [-0.06036957]
 [ 2.64924781]
 [-0.05418175]
 [-1.10353907]
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 [ 1.03393789]
 [-0.09796591]
 [ 0.13906751]
 [-0.10588241]
 [-1.01460673]
 [-0.30564965]
 [ 0.86292801]
 [-0.84183381]
 [-0.80075276]
 [-0.62527652]
 [ 0.14020469]
 [-0.35488642]
 [ 4.49442121]
 [-0.9493756 ]
 [-1.65146192]
 [ 0.3798793 ]
 [-0.30798122]
 [ 4.31583775]
 [-1.93093113]]
[[ -1.90534885e-02  -3.05150201e-01   2.72228379e-01 ...,  -2.32083003e-01
   -3.29084657e-01   2.91273540e-01]
 [  5.85405026e-02   1.46480694e-01  -1.04830005e-03 ...,  -2.22006478e-01
    1.63066603e+00   1.15785661e-01]
 [ -5.95369347e-02   2.67162888e-01   4.73291529e-01 ...,   2.39740570e-01
   -3.06371525e-01   9.59032127e-01]
 ..., 
 [ -1.83860671e-01  -2.36648323e-01  -3.84971724e-01 ...,   9.19443799e-02
   -5.96756718e-01  -3.28416070e-01]
 [ -2.74248173e-01  -1.77902484e-01  -1.76610442e-01 ...,  -1.16089825e-01
   -1.41448466e-01  -3.54582906e-01]
 [  3.86022731e-02   8.13717126e-02  -4.13713412e-02 ...,   5.23673784e-02
    2.90996111e+00  -8.13301800e-02]]
Progress: 81.3% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.15839024]
 [-0.94820754]
 [-1.19563674]
 [-0.76267195]
 [-0.0554263 ]
 [ 2.65364729]
 [-0.04854782]
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 [ 1.03777839]
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 [ 0.14358985]
 [-0.099877  ]
 [-1.01011833]
 [-0.30045007]
 [ 0.86818647]
 [-0.83621835]
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 [ 0.14441387]
 [-0.35007344]
 [ 4.49482436]
 [-0.94458683]
 [-1.64790156]
 [ 0.38434277]
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 [ 4.32545195]
 [-1.92830754]]
[[ -1.91547397e-02  -3.05684327e-01   2.72332921e-01 ...,  -2.32283567e-01
   -3.29174615e-01   2.90830667e-01]
 [  5.84634933e-02   1.46045297e-01  -1.20582329e-03 ...,  -2.22152244e-01
    1.63076842e+00   1.15119296e-01]
 [ -5.97987510e-02   2.65721024e-01   4.71413228e-01 ...,   2.39260549e-01
   -3.03384417e-01   9.56256331e-01]
 ..., 
 [ -1.83838986e-01  -2.36557745e-01  -3.85023931e-01 ...,   9.19824482e-02
   -5.97540910e-01  -3.28450432e-01]
 [ -2.74236330e-01  -1.77844928e-01  -1.76313715e-01 ...,  -1.16072936e-01
   -1.42144093e-01  -3.54593123e-01]
 [  3.84935137e-02   8.07415870e-02  -4.20008900e-02 ...,   5.21636398e-02
    2.91020330e+00  -8.24663914e-02]]
Progress: 81.3% ... Training loss: 0.062 ... Validation loss: 0.145[[-0.16245453]
 [-0.9519375 ]
 [-1.19690844]
 [-0.76710151]
 [-0.05957666]
 [ 2.65145474]
 [-0.05215324]
 [-1.10347175]
 [-0.53096171]
 [ 1.03612677]
 [-0.09731211]
 [ 0.13975541]
 [-0.10367868]
 [-1.01213624]
 [-0.30444063]
 [ 0.86374253]
 [-0.83975654]
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 [-0.62477337]
 [ 0.1407898 ]
 [-0.35373224]
 [ 4.49417297]
 [-0.94820118]
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 [ 4.31998295]
 [-1.92954978]]
[[ -1.90147538e-02  -3.04851031e-01   2.72753432e-01 ...,  -2.32027315e-01
   -3.32766714e-01   2.91787856e-01]
 [  5.84487248e-02   1.45954942e-01  -1.23756970e-03 ...,  -2.22180995e-01
    1.63084394e+00   1.15036113e-01]
 [ -5.97954769e-02   2.65748690e-01   4.71554187e-01 ...,   2.39260916e-01
   -3.04630870e-01   9.56648652e-01]
 ..., 
 [ -1.83762690e-01  -2.36113648e-01  -3.84672322e-01 ...,   9.21183936e-02
   -5.99955402e-01  -3.27730014e-01]
 [ -2.74305616e-01  -1.78256454e-01  -1.76792400e-01 ...,  -1.16198658e-01
   -1.42075624e-01  -3.55031064e-01]
 [  3.85808300e-02   8.12987049e-02  -4.16501060e-02 ...,   5.23230714e-02
    2.91035147e+00  -8.20713329e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1617845 ]
 [-0.95217878]
 [-1.19780767]
 [-0.76567594]
 [-0.0592606 ]
 [ 2.65274013]
 [-0.05056291]
 [-1.10302122]
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 [ 1.03644142]
 [-0.09618005]
 [ 0.13955468]
 [-0.10224552]
 [-1.00979121]
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 [ 0.86293742]
 [-0.83980077]
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 [ 0.14134691]
 [-0.3535009 ]
 [ 4.49497015]
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 [ 0.38173661]
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 [ 4.32057745]
 [-1.92857093]]
[[ -1.91838829e-02  -3.05763027e-01   2.71756204e-01 ...,  -2.32332301e-01
   -3.29798574e-01   2.90442107e-01]
 [  5.83686727e-02   1.45538575e-01  -1.61601727e-03 ...,  -2.22319477e-01
    1.63195035e+00   1.14427358e-01]
 [ -5.97707202e-02   2.65769532e-01   4.70976304e-01 ...,   2.39306283e-01
   -3.02553373e-01   9.55159771e-01]
 ..., 
 [ -1.83828578e-01  -2.36495209e-01  -3.84994222e-01 ...,   9.19942909e-02
   -5.98976742e-01  -3.28314348e-01]
 [ -2.74370610e-01  -1.78610525e-01  -1.77246572e-01 ...,  -1.16321491e-01
   -1.40910817e-01  -3.55626256e-01]
 [  3.87377794e-02   8.21688140e-02  -4.07096851e-02 ...,   5.26016363e-02
    2.91011113e+00  -8.11407013e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16050329]
 [-0.950084  ]
 [-1.19751329]
 [-0.76337231]
 [-0.05759634]
 [ 2.65256459]
 [-0.04936372]
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 [-0.52996712]
 [ 1.0359667 ]
 [-0.09459116]
 [ 0.14062093]
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 [ 0.86371708]
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 [ 0.14230551]
 [-0.35239133]
 [ 4.49490296]
 [-0.94499525]
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 [ 0.38202977]
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 [ 4.32393196]
 [-1.92872385]]
[[ -1.92058403e-02  -3.05928027e-01   2.71548287e-01 ...,  -2.32382312e-01
   -3.30893630e-01   2.90434848e-01]
 [  5.82995822e-02   1.45153408e-01  -2.07029752e-03 ...,  -2.22447136e-01
    1.63231545e+00   1.13665085e-01]
 [ -5.96582465e-02   2.66433929e-01   4.71536640e-01 ...,   2.39518046e-01
   -3.04244284e-01   9.55468701e-01]
 ..., 
 [ -1.83801010e-01  -2.36368306e-01  -3.84658094e-01 ...,   9.20449604e-02
   -5.99833696e-01  -3.28212625e-01]
 [ -2.74278331e-01  -1.78082850e-01  -1.76674475e-01 ...,  -1.16152652e-01
   -1.41908665e-01  -3.54968875e-01]
 [  3.86462175e-02   8.16449876e-02  -4.13763788e-02 ...,   5.24315257e-02
    2.91018174e+00  -8.16871511e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16165619]
 [-0.95213551]
 [-1.19743312]
 [-0.76477856]
 [-0.05832139]
 [ 2.64916573]
 [-0.05109006]
 [-1.10130611]
 [-0.53165373]
 [ 1.03663779]
 [-0.09444342]
 [ 0.13983617]
 [-0.10323976]
 [-1.01267259]
 [-0.30420049]
 [ 0.86276335]
 [-0.83896458]
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 [-0.62499358]
 [ 0.14108896]
 [-0.35316403]
 [ 4.49441634]
 [-0.94647666]
 [-1.64898889]
 [ 0.38066537]
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 [ 4.32125346]
 [-1.93056658]]
[[ -1.91286218e-02  -3.05413719e-01   2.72107162e-01 ...,  -2.32238962e-01
   -3.31623416e-01   2.91270620e-01]
 [  5.82701360e-02   1.44981727e-01  -2.24313543e-03 ...,  -2.22499935e-01
    1.63267112e+00   1.13450947e-01]
 [ -5.93618548e-02   2.68028998e-01   4.73118589e-01 ...,   2.40059840e-01
   -3.08061295e-01   9.58039233e-01]
 ..., 
 [ -1.83783842e-01  -2.36239841e-01  -3.84561251e-01 ...,   9.20797373e-02
   -5.99769228e-01  -3.28125894e-01]
 [ -2.74188566e-01  -1.77552348e-01  -1.76065842e-01 ...,  -1.15989365e-01
   -1.43252196e-01  -3.54028198e-01]
 [  3.86892007e-02   8.18787515e-02  -4.11852678e-02 ...,   5.25025151e-02
    2.91001840e+00  -8.14396848e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16120976]
 [-0.95132396]
 [-1.19689233]
 [-0.7643036 ]
 [-0.05794535]
 [ 2.65093527]
 [-0.05005193]
 [-1.10086731]
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 [ 1.0363725 ]
 [-0.09386984]
 [ 0.14079407]
 [-0.10274788]
 [-1.01240504]
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 [ 0.86409757]
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 [ 0.14130923]
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 [ 4.49446532]
 [-0.94669665]
 [-1.64889289]
 [ 0.38173812]
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 [ 4.32246234]
 [-1.93031457]]
[[ -1.92084717e-02  -3.05900286e-01   2.71841593e-01 ...,  -2.32388281e-01
   -3.30412710e-01   2.90350225e-01]
 [  5.83026294e-02   1.45157691e-01  -2.05662274e-03 ...,  -2.22445969e-01
    1.63252529e+00   1.13572901e-01]
 [ -5.94833503e-02   2.67379672e-01   4.72423817e-01 ...,   2.39861531e-01
   -3.08153108e-01   9.57232399e-01]
 ..., 
 [ -1.83810286e-01  -2.36387949e-01  -3.84752153e-01 ...,   9.20283930e-02
   -5.99756411e-01  -3.28437150e-01]
 [ -2.74226619e-01  -1.77784279e-01  -1.76296133e-01 ...,  -1.16064869e-01
   -1.43361180e-01  -3.54412700e-01]
 [  3.86742843e-02   8.17822554e-02  -4.11984737e-02 ...,   5.24754273e-02
    2.91018090e+00  -8.13301723e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15701168]
 [-0.94783609]
 [-1.19451917]
 [-0.75958251]
 [-0.05403106]
 [ 2.65143404]
 [-0.04648295]
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 [ 0.14427843]
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 [-1.01053574]
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 [ 0.86732867]
 [-0.83440259]
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 [ 0.14475747]
 [-0.34973247]
 [ 4.49472692]
 [-0.94258595]
 [-1.64386661]
 [ 0.38402895]
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 [ 4.32928767]
 [-1.92909882]]
[[ -1.91844789e-02  -3.05779462e-01   2.71981016e-01 ...,  -2.32346780e-01
   -3.31287222e-01   2.90800380e-01]
 [  5.82712009e-02   1.44972907e-01  -2.19551695e-03 ...,  -2.22502282e-01
    1.63268436e+00   1.13306776e-01]
 [ -5.93554054e-02   2.68082790e-01   4.72379540e-01 ...,   2.40072163e-01
   -3.09587987e-01   9.56882007e-01]
 ..., 
 [ -1.83852139e-01  -2.36634848e-01  -3.84918270e-01 ...,   9.19502153e-02
   -5.98836521e-01  -3.28646674e-01]
 [ -2.74312620e-01  -1.78248567e-01  -1.76844760e-01 ...,  -1.16223956e-01
   -1.43055081e-01  -3.55399981e-01]
 [  3.86152135e-02   8.14347592e-02  -4.15543928e-02 ...,   5.23680029e-02
    2.91018742e+00  -8.14661261e-02]]
Progress: 81.3% ... Training loss: 0.063 ... Validation loss: 0.147[[-0.1668483 ]
 [-0.95587837]
 [-1.19988434]
 [-0.76946467]
 [-0.06295051]
 [ 2.64712379]
 [-0.05504873]
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 [ 1.03349697]
 [-0.09887678]
 [ 0.13592637]
 [-0.10856315]
 [-1.01630033]
 [-0.30805978]
 [ 0.8577549 ]
 [-0.84350184]
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 [ 0.13677979]
 [-0.3586885 ]
 [ 4.49288757]
 [-0.95109291]
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 [ 0.37727157]
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 [ 4.31396106]
 [-1.93223367]]
[[ -1.89003626e-02  -3.04183331e-01   2.73360652e-01 ...,  -2.31834133e-01
   -3.34840690e-01   2.92538636e-01]
 [  5.83458261e-02   1.45413157e-01  -1.92454580e-03 ...,  -2.22376658e-01
    1.63249531e+00   1.13635740e-01]
 [ -5.93681997e-02   2.68007524e-01   4.73395931e-01 ...,   2.40056997e-01
   -3.12427604e-01   9.59228220e-01]
 ..., 
 [ -1.83756383e-01  -2.36107610e-01  -3.84509499e-01 ...,   9.21179879e-02
   -6.00259278e-01  -3.27965604e-01]
 [ -2.74250344e-01  -1.77913603e-01  -1.76381798e-01 ...,  -1.16107989e-01
   -1.44097372e-01  -3.54900094e-01]
 [  3.86894273e-02   8.18690124e-02  -4.11471759e-02 ...,   5.25015126e-02
    2.91013621e+00  -8.12988585e-02]]
Progress: 81.3% ... Training loss: 0.067 ... Validation loss: 0.137[[-0.15995667]
 [-0.94979276]
 [-1.19467104]
 [-0.76351724]
 [-0.05799063]
 [ 2.65219549]
 [-0.04868622]
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 [-0.52864755]
 [ 1.03821779]
 [-0.09293591]
 [ 0.14197456]
 [-0.10145456]
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 [ 0.86461593]
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 [ 0.1428408 ]
 [-0.35241955]
 [ 4.49396147]
 [-0.94479983]
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 [ 0.38303614]
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 [ 4.32423466]
 [-1.92755796]]
[[ -1.92123490e-02  -3.05901143e-01   2.71676060e-01 ...,  -2.32392146e-01
   -3.28739763e-01   2.89527255e-01]
 [  5.82989136e-02   1.45144058e-01  -2.27119643e-03 ...,  -2.22457315e-01
    1.63335992e+00   1.13105487e-01]
 [ -5.98040861e-02   2.65511768e-01   4.70472239e-01 ...,   2.39291177e-01
   -3.04052184e-01   9.53775100e-01]
 ..., 
 [ -1.83902645e-01  -2.36923348e-01  -3.85336998e-01 ...,   9.18572742e-02
   -5.97920045e-01  -3.29143736e-01]
 [ -2.74392027e-01  -1.78700497e-01  -1.77285682e-01 ...,  -1.16351478e-01
   -1.40646269e-01  -3.56403607e-01]
 [  3.87739082e-02   8.23502718e-02  -4.07589314e-02 ...,   5.26596650e-02
    2.91003551e+00  -8.07035051e-02]]
Progress: 81.3% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.1576234 ]
 [-0.94736222]
 [-1.19240799]
 [-0.7616551 ]
 [-0.0562143 ]
 [ 2.65347058]
 [-0.04637889]
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 [ 1.03974556]
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 [ 0.14431593]
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 [ 4.49567601]
 [-0.94298079]
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 [ 0.38477727]
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 [ 4.32760495]
 [-1.92587151]]
[[ -1.94199815e-02  -3.07061162e-01   2.70390207e-01 ...,  -2.32768597e-01
   -3.25406342e-01   2.87804612e-01]
 [  5.83199647e-02   1.45266631e-01  -2.13363061e-03 ...,  -2.22419053e-01
    1.63307557e+00   1.13204870e-01]
 [ -5.99326941e-02   2.64812845e-01   4.69650253e-01 ...,   2.39059924e-01
   -3.02443813e-01   9.52545629e-01]
 ..., 
 [ -1.83993974e-01  -2.37461988e-01  -3.85934979e-01 ...,   9.16940577e-02
   -5.96642798e-01  -3.29898650e-01]
 [ -2.74395071e-01  -1.78653826e-01  -1.77146114e-01 ...,  -1.16342331e-01
   -1.40136459e-01  -3.56506234e-01]
 [  3.87695825e-02   8.23337107e-02  -4.07920691e-02 ...,   5.26603895e-02
    2.90989849e+00  -8.09787539e-02]]
Progress: 81.3% ... Training loss: 0.065 ... Validation loss: 0.146[[-0.16526349]
 [-0.95443091]
 [-1.19886756]
 [-0.76764869]
 [-0.06184286]
 [ 2.64765166]
 [-0.05354974]
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 [-0.53469697]
 [ 1.0345609 ]
 [-0.09753135]
 [ 0.13774128]
 [-0.10594643]
 [-1.01419134]
 [-0.30645574]
 [ 0.85979845]
 [-0.84253569]
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 [ 0.13887321]
 [-0.35603244]
 [ 4.49451217]
 [-0.94944154]
 [-1.65237615]
 [ 0.37854663]
 [-0.30920859]
 [ 4.31581791]
 [-1.93066271]]
[[ -1.91524318e-02  -3.05506811e-01   2.72203820e-01 ...,  -2.32282042e-01
   -3.30276918e-01   2.90578679e-01]
 [  5.83165447e-02   1.45245499e-01  -2.14072567e-03 ...,  -2.22425625e-01
    1.63305973e+00   1.13208810e-01]
 [ -5.94777055e-02   2.67490948e-01   4.72885715e-01 ...,   2.39927793e-01
   -3.10982570e-01   9.58148581e-01]
 ..., 
 [ -1.83939814e-01  -2.37151204e-01  -3.85666724e-01 ...,   9.17975198e-02
   -5.97513688e-01  -3.29300679e-01]
 [ -2.74267250e-01  -1.77903047e-01  -1.76455412e-01 ...,  -1.16100340e-01
   -1.42502866e-01  -3.55359765e-01]
 [  3.88387580e-02   8.27378576e-02  -4.02274248e-02 ...,   5.27876174e-02
    2.90978514e+00  -8.03927672e-02]]
Progress: 81.3% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.1580533 ]
 [-0.94773795]
 [-1.19369553]
 [-0.76109448]
 [-0.05558291]
 [ 2.65028597]
 [-0.04722659]
 [-1.09912663]
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 [ 1.03978126]
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 [ 0.14435717]
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 [-1.00964005]
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 [-0.34922291]
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 [ 0.38390586]
 [-0.30261468]
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 [-1.92800231]]
[[ -1.92874251e-02  -3.06192494e-01   2.71474476e-01 ...,  -2.32512284e-01
   -3.27258402e-01   2.89352428e-01]
 [  5.82978264e-02   1.45138284e-01  -2.23595261e-03 ...,  -2.22459188e-01
    1.63324154e+00   1.13087368e-01]
 [ -5.95279894e-02   2.67120696e-01   4.71741497e-01 ...,   2.39801417e-01
   -3.08151935e-01   9.55595471e-01]
 ..., 
 [ -1.84096048e-01  -2.38011867e-01  -3.86338522e-01 ...,   9.15097240e-02
   -5.94861365e-01  -3.30391778e-01]
 [ -2.74262848e-01  -1.77828678e-01  -1.76522863e-01 ...,  -1.16081485e-01
   -1.41848303e-01  -3.55460153e-01]
 [  3.87884932e-02   8.24429867e-02  -4.03979684e-02 ...,   5.26891029e-02
    2.90971566e+00  -8.09372771e-02]]
Progress: 81.3% ... Training loss: 0.063 ... Validation loss: 0.145[[-0.16150148]
 [-0.9504727 ]
 [-1.19721913]
 [-0.76419149]
 [-0.05868602]
 [ 2.65070028]
 [-0.05010538]
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 [-0.53136362]
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 [-0.09383204]
 [ 0.14113568]
 [-0.10176754]
 [-1.01115345]
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 [ 0.86334591]
 [-0.83910313]
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 [ 0.14319253]
 [-0.35257115]
 [ 4.49526452]
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 [ 0.38173283]
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 [-1.92846362]]
[[ -1.93060448e-02  -3.06387418e-01   2.71242343e-01 ...,  -2.32544400e-01
   -3.28761678e-01   2.89231872e-01]
 [  5.83226149e-02   1.45278555e-01  -2.16876228e-03 ...,  -2.22417515e-01
    1.63310578e+00   1.13165393e-01]
 [ -5.95903540e-02   2.66767641e-01   4.71364351e-01 ...,   2.39702388e-01
   -3.07813398e-01   9.54792438e-01]
 ..., 
 [ -1.83962329e-01  -2.37236301e-01  -3.85667305e-01 ...,   9.17557247e-02
   -5.96660104e-01  -3.29666849e-01]
 [ -2.74189036e-01  -1.77429678e-01  -1.76215591e-01 ...,  -1.15952931e-01
   -1.42602411e-01  -3.54930409e-01]
 [  3.87627038e-02   8.22774043e-02  -4.05928832e-02 ...,   5.26383266e-02
    2.90968733e+00  -8.13052348e-02]]
Progress: 81.4% ... Training loss: 0.060 ... Validation loss: 0.139[[-0.16129566]
 [-0.94951569]
 [-1.19681734]
 [-0.76371676]
 [-0.05822747]
 [ 2.65011764]
 [-0.05005569]
 [-1.10180029]
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 [ 1.03651908]
 [-0.09357237]
 [ 0.14180492]
 [-0.10105905]
 [-1.01189039]
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 [-0.83828567]
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 [-0.35193314]
 [ 4.49518159]
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 [ 0.38093513]
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 [ 4.32271037]
 [-1.92868475]]
[[ -1.92723841e-02  -3.06221322e-01   2.71413380e-01 ...,  -2.32492644e-01
   -3.29519274e-01   2.89895730e-01]
 [  5.83285225e-02   1.45310107e-01  -2.13313667e-03 ...,  -2.22407723e-01
    1.63307892e+00   1.13218503e-01]
 [ -5.95270585e-02   2.67180475e-01   4.71727798e-01 ...,   2.39823316e-01
   -3.09218096e-01   9.55180509e-01]
 ..., 
 [ -1.84014902e-01  -2.37519271e-01  -3.85967994e-01 ...,   9.16615629e-02
   -5.95540697e-01  -3.30065906e-01]
 [ -2.74157540e-01  -1.77254156e-01  -1.76113437e-01 ...,  -1.15903392e-01
   -1.42970694e-01  -3.54640133e-01]
 [  3.87293857e-02   8.20822995e-02  -4.07682295e-02 ...,   5.25765543e-02
    2.90970013e+00  -8.15551334e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16769038]
 [-0.95465613]
 [-1.20205645]
 [-0.76789729]
 [-0.0631645 ]
 [ 2.64823252]
 [-0.05477248]
 [-1.10679093]
 [-0.53661241]
 [ 1.03077367]
 [-0.09909123]
 [ 0.13610909]
 [-0.10591479]
 [-1.0143889 ]
 [-0.30756581]
 [ 0.85633666]
 [-0.84465479]
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 [ 0.13843369]
 [-0.35831983]
 [ 4.49331223]
 [-0.94945869]
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 [ 0.37655926]
 [-0.30962572]
 [ 4.31324945]
 [-1.93043199]]
[[ -1.91109193e-02  -3.05369157e-01   2.72117369e-01 ...,  -2.32216578e-01
   -3.32848792e-01   2.90950582e-01]
 [  5.82688718e-02   1.44962227e-01  -2.25484734e-03 ...,  -2.22516845e-01
    1.63322181e+00   1.12922238e-01]
 [ -5.95783755e-02   2.66973105e-01   4.71440506e-01 ...,   2.39746895e-01
   -3.08823006e-01   9.55944834e-01]
 ..., 
 [ -1.83906253e-01  -2.36908732e-01  -3.85494449e-01 ...,   9.18658272e-02
   -5.97737119e-01  -3.29389689e-01]
 [ -2.74186873e-01  -1.77467364e-01  -1.75823878e-01 ...,  -1.15968807e-01
   -1.42281056e-01  -3.54811971e-01]
 [  3.87795642e-02   8.23780627e-02  -4.04225424e-02 ...,   5.26664974e-02
    2.90958386e+00  -8.09635757e-02]]
Progress: 81.4% ... Training loss: 0.065 ... Validation loss: 0.138[[-0.15932336]
 [-0.9486814 ]
 [-1.19481316]
 [-0.76131235]
 [-0.05597952]
 [ 2.64717347]
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 [ 1.03816349]
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 [ 0.14276174]
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 [-1.01163352]
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 [ 0.86446637]
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 [-0.35148233]
 [ 4.49397153]
 [-0.94461384]
 [-1.64533408]
 [ 0.38122547]
 [-0.30422136]
 [ 4.32584475]
 [-1.92888322]]
[[ -1.92083515e-02  -3.05824815e-01   2.71340483e-01 ...,  -2.32367055e-01
   -3.32607447e-01   2.90883869e-01]
 [  5.81979416e-02   1.44578992e-01  -2.57214815e-03 ...,  -2.22642908e-01
    1.63378310e+00   1.12387251e-01]
 [ -5.93788623e-02   2.67919795e-01   4.71891942e-01 ...,   2.40089615e-01
   -3.08324226e-01   9.56357233e-01]
 ..., 
 [ -1.83963535e-01  -2.37214033e-01  -3.85779058e-01 ...,   9.17799298e-02
   -5.96901232e-01  -3.29621851e-01]
 [ -2.74262602e-01  -1.77870066e-01  -1.76016568e-01 ...,  -1.16106770e-01
   -1.40947778e-01  -3.54969986e-01]
 [  3.87753906e-02   8.23605018e-02  -4.04802901e-02 ...,   5.26609886e-02
    2.90958778e+00  -8.10640019e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16546977]
 [-0.95272544]
 [-1.20053578]
 [-0.76538152]
 [-0.06046981]
 [ 2.6442727 ]
 [-0.05300659]
 [-1.10491458]
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 [ 1.03459901]
 [-0.09640844]
 [ 0.13740899]
 [-0.10482676]
 [-1.01498249]
 [-0.30578177]
 [ 0.85768523]
 [-0.84221513]
 [-0.80262842]
 [-0.62737388]
 [ 0.13974974]
 [-0.3562446 ]
 [ 4.49317939]
 [-0.94814715]
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 [ 0.37706217]
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 [ 4.31677901]
 [-1.93123356]]
[[ -1.89235077e-02  -3.04249972e-01   2.73278241e-01 ...,  -2.31850196e-01
   -3.37091943e-01   2.93033137e-01]
 [  5.81483892e-02   1.44290471e-01  -2.81780772e-03 ...,  -2.22739529e-01
    1.63383214e+00   1.12224427e-01]
 [ -5.93902107e-02   2.67881043e-01   4.72145718e-01 ...,   2.40089855e-01
   -3.08672748e-01   9.58159698e-01]
 ..., 
 [ -1.84012819e-01  -2.37547970e-01  -3.85935990e-01 ...,   9.16981942e-02
   -5.96720802e-01  -3.30435507e-01]
 [ -2.74224555e-01  -1.77636329e-01  -1.75686647e-01 ...,  -1.16045079e-01
   -1.42278167e-01  -3.54656825e-01]
 [  3.88960681e-02   8.30589624e-02  -3.99071809e-02 ...,   5.28888478e-02
    2.90940055e+00  -8.02461681e-02]]
Progress: 81.4% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.16253588]
 [-0.95014066]
 [-1.19856795]
 [-0.76220479]
 [-0.05735841]
 [ 2.64512934]
 [-0.05040712]
 [-1.10185468]
 [-0.53216866]
 [ 1.03629909]
 [-0.09375954]
 [ 0.14012292]
 [-0.10153827]
 [-1.0135052 ]
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 [ 0.86085125]
 [-0.83940495]
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 [ 0.14244065]
 [-0.35366064]
 [ 4.49326202]
 [-0.94612854]
 [-1.64835957]
 [ 0.37914015]
 [-0.30610932]
 [ 4.32163678]
 [-1.92994045]]
[[ -1.89710350e-02  -3.04483443e-01   2.73010637e-01 ...,  -2.31923261e-01
   -3.36758838e-01   2.92373061e-01]
 [  5.81069134e-02   1.44059467e-01  -2.87984503e-03 ...,  -2.22812375e-01
    1.63377776e+00   1.11905868e-01]
 [ -5.92877544e-02   2.68431614e-01   4.72299956e-01 ...,   2.40294215e-01
   -3.08291820e-01   9.57926858e-01]
 ..., 
 [ -1.84022381e-01  -2.37630885e-01  -3.85861318e-01 ...,   9.17023030e-02
   -5.97238218e-01  -3.30499086e-01]
 [ -2.74261905e-01  -1.77864897e-01  -1.75715072e-01 ...,  -1.16115477e-01
   -1.41422544e-01  -3.54885314e-01]
 [  3.87560700e-02   8.22543772e-02  -4.08090821e-02 ...,   5.26299430e-02
    2.90971287e+00  -8.15963301e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16306255]
 [-0.95031422]
 [-1.19776771]
 [-0.76292851]
 [-0.05795708]
 [ 2.6450416 ]
 [-0.05156657]
 [-1.10314092]
 [-0.53275105]
 [ 1.0358865 ]
 [-0.094346  ]
 [ 0.13913118]
 [-0.10223045]
 [-1.01429797]
 [-0.30334045]
 [ 0.86001358]
 [-0.83942588]
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 [ 0.14236086]
 [-0.3546453 ]
 [ 4.49358268]
 [-0.94578876]
 [-1.64866093]
 [ 0.37833288]
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 [ 4.32140835]
 [-1.92992736]]
[[ -1.90474700e-02  -3.04873212e-01   2.72725992e-01 ...,  -2.32084500e-01
   -3.38598708e-01   2.92173170e-01]
 [  5.82482002e-02   1.44893101e-01  -2.20141030e-03 ...,  -2.22558941e-01
    1.63226276e+00   1.13155603e-01]
 [ -5.93101559e-02   2.68350640e-01   4.72454497e-01 ...,   2.40253927e-01
   -3.10359836e-01   9.57648900e-01]
 ..., 
 [ -1.83950711e-01  -2.37219766e-01  -3.85513146e-01 ...,   9.18295748e-02
   -5.98000461e-01  -3.29987169e-01]
 [ -2.74295385e-01  -1.78052839e-01  -1.75997409e-01 ...,  -1.16178478e-01
   -1.41459290e-01  -3.55301686e-01]
 [  3.87291891e-02   8.20973550e-02  -4.08064070e-02 ...,   5.25722524e-02
    2.90964726e+00  -8.16954724e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16405097]
 [-0.95147852]
 [-1.20111349]
 [-0.76297173]
 [-0.05899883]
 [ 2.64690055]
 [-0.05044774]
 [-1.10377512]
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 [ 1.03452823]
 [-0.09509103]
 [ 0.13843963]
 [-0.10225063]
 [-1.01172535]
 [-0.30517572]
 [ 0.85787585]
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 [-0.62896777]
 [ 0.14138265]
 [-0.35595867]
 [ 4.49379302]
 [-0.94380757]
 [-1.65205668]
 [ 0.37862898]
 [-0.30738728]
 [ 4.31846564]
 [-1.92909223]]
[[ -1.90283872e-02  -3.04746032e-01   2.72953028e-01 ...,  -2.32040291e-01
   -3.36745415e-01   2.91712139e-01]
 [  5.81674744e-02   1.44430768e-01  -2.68486931e-03 ...,  -2.22692541e-01
    1.63305653e+00   1.12288654e-01]
 [ -5.94145946e-02   2.67730157e-01   4.71904548e-01 ...,   2.40092267e-01
   -3.06942066e-01   9.56589600e-01]
 ..., 
 [ -1.84012367e-01  -2.37575285e-01  -3.85770355e-01 ...,   9.17191506e-02
   -5.96230288e-01  -3.30546648e-01]
 [ -2.74345893e-01  -1.78363126e-01  -1.76248405e-01 ...,  -1.16273429e-01
   -1.40694075e-01  -3.56004874e-01]
 [  3.88762793e-02   8.29402992e-02  -3.98870065e-02 ...,   5.28450770e-02
    2.90938230e+00  -8.04641917e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16271783]
 [-0.95082506]
 [-1.20159553]
 [-0.76177671]
 [-0.05873187]
 [ 2.64630503]
 [-0.04982318]
 [-1.10232647]
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 [ 1.03503223]
 [-0.09424751]
 [ 0.13909263]
 [-0.10176021]
 [-1.0120233 ]
 [-0.30433561]
 [ 0.85832731]
 [-0.84043971]
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 [ 0.14213678]
 [-0.35457849]
 [ 4.49405134]
 [-0.94305631]
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 [ 0.37902611]
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 [ 4.32080863]
 [-1.92911954]]
[[ -1.89947035e-02  -3.04568814e-01   2.72824688e-01 ...,  -2.31986315e-01
   -3.38500150e-01   2.92163951e-01]
 [  5.81630584e-02   1.44407513e-01  -2.69432600e-03 ...,  -2.22700523e-01
    1.63308887e+00   1.12276920e-01]
 [ -5.92959358e-02   2.68412049e-01   4.72574247e-01 ...,   2.40306266e-01
   -3.08925936e-01   9.57676077e-01]
 ..., 
 [ -1.84048258e-01  -2.37769559e-01  -3.85956023e-01 ...,   9.16587512e-02
   -5.95465467e-01  -3.30898926e-01]
 [ -2.74345511e-01  -1.78368127e-01  -1.76276836e-01 ...,  -1.16267356e-01
   -1.40734932e-01  -3.55927115e-01]
 [  3.88496255e-02   8.27495853e-02  -4.00620472e-02 ...,   5.27821995e-02
    2.90937996e+00  -8.05928054e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15843911]
 [-0.94689275]
 [-1.19765787]
 [-0.75842884]
 [-0.05572317]
 [ 2.64788756]
 [-0.0464796 ]
 [-1.09959323]
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 [ 1.03740584]
 [-0.09083351]
 [ 0.14286035]
 [-0.09797199]
 [-1.00993895]
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 [ 0.86280175]
 [-0.83574609]
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 [-0.6247    ]
 [ 0.14587124]
 [-0.3508667 ]
 [ 4.49453704]
 [-0.94077817]
 [-1.64596459]
 [ 0.38210308]
 [-0.30379661]
 [ 4.3280574 ]
 [-1.92776496]]
[[ -1.91689225e-02  -3.05575416e-01   2.72101382e-01 ...,  -2.32308189e-01
   -3.37102516e-01   2.91140167e-01]
 [  5.81722719e-02   1.44454759e-01  -2.68263959e-03 ...,  -2.22685633e-01
    1.63303330e+00   1.12288423e-01]
 [ -5.93572106e-02   2.68050461e-01   4.72354656e-01 ...,   2.40172769e-01
   -3.08602895e-01   9.57092779e-01]
 ..., 
 [ -1.84071300e-01  -2.37911777e-01  -3.86152229e-01 ...,   9.16164086e-02
   -5.94820992e-01  -3.31241219e-01]
 [ -2.74468896e-01  -1.79052283e-01  -1.76829382e-01 ...,  -1.16496230e-01
   -1.37544407e-01  -3.56697848e-01]
 [  3.87553401e-02   8.22255684e-02  -4.06233070e-02 ...,   5.26016845e-02
    2.90941752e+00  -8.11767225e-02]]
Progress: 81.4% ... Training loss: 0.062 ... Validation loss: 0.143[[-0.16028244]
 [-0.94699256]
 [-1.19621169]
 [-0.76100305]
 [-0.05680776]
 [ 2.6479577 ]
 [-0.04804722]
 [-1.10067772]
 [-0.53094201]
 [ 1.03724551]
 [-0.09229133]
 [ 0.14217343]
 [-0.09931976]
 [-1.01224803]
 [-0.30020027]
 [ 0.86341753]
 [-0.83646407]
 [-0.79892454]
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 [ 0.14414759]
 [-0.35160336]
 [ 4.49427467]
 [-0.94526383]
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 [ 0.38138481]
 [-0.30424242]
 [ 4.32653701]
 [-1.92892132]]
[[ -1.92078927e-02  -3.05836475e-01   2.71589074e-01 ...,  -2.32398565e-01
   -3.37541992e-01   2.91236928e-01]
 [  5.82189350e-02   1.44733158e-01  -2.41509835e-03 ...,  -2.22605242e-01
    1.63265356e+00   1.12625476e-01]
 [ -5.93879200e-02   2.67937664e-01   4.72635553e-01 ...,   2.40114689e-01
   -3.11638336e-01   9.58217872e-01]
 ..., 
 [ -1.83940177e-01  -2.37162197e-01  -3.85400578e-01 ...,   9.18608052e-02
   -5.96339559e-01  -3.30236648e-01]
 [ -2.74339705e-01  -1.78306200e-01  -1.76113983e-01 ...,  -1.16259414e-01
   -1.39312951e-01  -3.55905113e-01]
 [  3.87011970e-02   8.19211929e-02  -4.12743558e-02 ...,   5.24943795e-02
    2.90964058e+00  -8.15732665e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.15966279]
 [-0.94586893]
 [-1.19397803]
 [-0.76186841]
 [-0.05749905]
 [ 2.64984562]
 [-0.04754561]
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 [ 1.03918356]
 [-0.09201737]
 [ 0.14218205]
 [-0.09945611]
 [-1.01085656]
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 [ 0.86380058]
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 [ 0.14405563]
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 [ 4.49458113]
 [-0.94564391]
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 [ 0.38239859]
 [-0.30336704]
 [ 4.3274365 ]
 [-1.92798385]]
[[ -1.91438855e-02  -3.05430439e-01   2.71414571e-01 ...,  -2.32289103e-01
   -3.38307990e-01   2.91561635e-01]
 [  5.81942345e-02   1.44589228e-01  -2.63190128e-03 ...,  -2.22650139e-01
    1.63271112e+00   1.12427812e-01]
 [ -5.97292254e-02   2.66057564e-01   4.70742178e-01 ...,   2.39469514e-01
   -3.08913428e-01   9.55413666e-01]
 ..., 
 [ -1.83960622e-01  -2.37302243e-01  -3.85513362e-01 ...,   9.18191260e-02
   -5.96434720e-01  -3.30207512e-01]
 [ -2.74158872e-01  -1.77279589e-01  -1.75355615e-01 ...,  -1.15943912e-01
   -1.40878522e-01  -3.54366814e-01]
 [  3.87388398e-02   8.21450931e-02  -4.11526574e-02 ...,   5.25609658e-02
    2.90953630e+00  -8.13554901e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16709762]
 [-0.95100134]
 [-1.19728167]
 [-0.76931101]
 [-0.06408414]
 [ 2.64854494]
 [-0.05354532]
 [-1.10920914]
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 [ 1.03637741]
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 [ 0.13705214]
 [-0.10516823]
 [-1.01406193]
 [-0.30514948]
 [ 0.85728199]
 [-0.84143326]
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 [-0.62647659]
 [ 0.13830893]
 [-0.35650597]
 [ 4.49153323]
 [-0.9521119 ]
 [-1.65711729]
 [ 0.37769353]
 [-0.30853936]
 [ 4.3163131 ]
 [-1.93063921]]
[[ -1.89005125e-02  -3.03951809e-01   2.73112870e-01 ...,  -2.31830640e-01
   -3.41282136e-01   2.93615679e-01]
 [  5.82135806e-02   1.44714229e-01  -2.47544949e-03 ...,  -2.22612732e-01
    1.63191325e+00   1.12619083e-01]
 [ -5.98902702e-02   2.65190629e-01   4.70600089e-01 ...,   2.39177823e-01
   -3.10489450e-01   9.56148458e-01]
 ..., 
 [ -1.83887203e-01  -2.36895977e-01  -3.85138825e-01 ...,   9.19590079e-02
   -5.97906341e-01  -3.29705814e-01]
 [ -2.74048636e-01  -1.76658191e-01  -1.74640018e-01 ...,  -1.15752326e-01
   -1.41607859e-01  -3.53203696e-01]
 [  3.87198954e-02   8.20598018e-02  -4.13472398e-02 ...,   5.25192457e-02
    2.90982548e+00  -8.18708973e-02]]
Progress: 81.4% ... Training loss: 0.064 ... Validation loss: 0.136[[-0.16118787]
 [-0.94684651]
 [-1.19337132]
 [-0.76396197]
 [-0.05855306]
 [ 2.65128911]
 [-0.0486343 ]
 [-1.10361946]
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 [ 1.04156134]
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 [ 0.14274522]
 [-0.09956169]
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 [ 0.86421494]
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 [ 0.14346185]
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 [ 4.49164437]
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 [-1.65114534]
 [ 0.3815977 ]
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 [ 4.32430912]
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[[ -1.90393139e-02  -3.04648039e-01   2.72611506e-01 ...,  -2.32099828e-01
   -3.36520937e-01   2.92921748e-01]
 [  5.83003966e-02   1.45239412e-01  -1.85844486e-03 ...,  -2.22469968e-01
    1.63203036e+00   1.13723813e-01]
 [ -5.97619795e-02   2.65988379e-01   4.71641339e-01 ...,   2.39370438e-01
   -3.06338189e-01   9.56215462e-01]
 ..., 
 [ -1.83954568e-01  -2.37259474e-01  -3.85592830e-01 ...,   9.18360824e-02
   -5.96525105e-01  -3.30259909e-01]
 [ -2.74049288e-01  -1.76679250e-01  -1.74448274e-01 ...,  -1.15758491e-01
   -1.41081154e-01  -3.53127358e-01]
 [  3.86697347e-02   8.17608495e-02  -4.15103558e-02 ...,   5.24266309e-02
    2.90977688e+00  -8.23838702e-02]]
Progress: 81.4% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16486232]
 [-0.95091364]
 [-1.19887354]
 [-0.7661611 ]
 [-0.06020974]
 [ 2.64852094]
 [-0.05161146]
 [-1.10357121]
 [-0.53541005]
 [ 1.03929253]
 [-0.09679322]
 [ 0.13990748]
 [-0.10226831]
 [-1.01473568]
 [-0.30436308]
 [ 0.86133849]
 [-0.84093092]
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 [ 0.14042917]
 [-0.35383005]
 [ 4.49018855]
 [-0.94920553]
 [-1.65283423]
 [ 0.37870185]
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 [ 4.31688977]
 [-1.93306322]]
[[ -1.88232527e-02  -3.03290282e-01   2.74292039e-01 ...,  -2.31697438e-01
   -3.35897392e-01   2.96106018e-01]
 [  5.83407767e-02   1.45502292e-01  -1.49727266e-03 ...,  -2.22403878e-01
    1.63209598e+00   1.14378954e-01]
 [ -5.93080034e-02   2.68572301e-01   4.74360131e-01 ...,   2.40204487e-01
   -3.07796131e-01   9.60733103e-01]
 ..., 
 [ -1.84043612e-01  -2.37757401e-01  -3.86015180e-01 ...,   9.16785394e-02
   -5.94378182e-01  -3.30976125e-01]
 [ -2.73908896e-01  -1.75863019e-01  -1.73528659e-01 ...,  -1.15497156e-01
   -1.42194926e-01  -3.51657039e-01]
 [  3.86463800e-02   8.16078013e-02  -4.17331057e-02 ...,   5.23761700e-02
    2.90989156e+00  -8.23751372e-02]]
Progress: 81.4% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.1613238 ]
 [-0.94858561]
 [-1.19633907]
 [-0.76442128]
 [-0.05864379]
 [ 2.65062731]
 [-0.04883349]
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 [ 1.04201521]
 [-0.09419966]
 [ 0.14311186]
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 [-1.01274711]
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 [ 0.86518672]
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 [-0.79750444]
 [-0.62282988]
 [ 0.14323524]
 [-0.35047538]
 [ 4.49114319]
 [-0.9468013 ]
 [-1.64931144]
 [ 0.3811796 ]
 [-0.30528778]
 [ 4.32271666]
 [-1.93151183]]
[[ -1.89839527e-02  -3.04172220e-01   2.73277663e-01 ...,  -2.31982157e-01
   -3.34503970e-01   2.94875160e-01]
 [  5.83747065e-02   1.45685166e-01  -1.33092861e-03 ...,  -2.22348360e-01
    1.63186257e+00   1.14640015e-01]
 [ -5.93353808e-02   2.68444785e-01   4.73881081e-01 ...,   2.40177461e-01
   -3.05833560e-01   9.59661340e-01]
 ..., 
 [ -1.84150170e-01  -2.38348599e-01  -3.86542093e-01 ...,   9.14943211e-02
   -5.93216238e-01  -3.31511300e-01]
 [ -2.74028879e-01  -1.76541140e-01  -1.74126328e-01 ...,  -1.15714601e-01
   -1.40461221e-01  -3.53005977e-01]
 [  3.85214821e-02   8.09008323e-02  -4.25010933e-02 ...,   5.21427924e-02
    2.91031981e+00  -8.36606022e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.15695651]
 [-0.94465925]
 [-1.19214621]
 [-0.76164917]
 [-0.05597292]
 [ 2.65596281]
 [-0.04416712]
 [-1.10156631]
 [-0.52721939]
 [ 1.04347379]
 [-0.09072765]
 [ 0.1466595 ]
 [-0.09439763]
 [-1.00706881]
 [-0.29703071]
 [ 0.86962331]
 [-0.83352293]
 [-0.79407082]
 [-0.61934994]
 [ 0.14669091]
 [-0.34736804]
 [ 4.49288748]
 [-0.94385323]
 [-1.64935906]
 [ 0.38562423]
 [-0.30058828]
 [ 4.32890381]
 [-1.92738245]]
[[ -1.93040893e-02  -3.06003150e-01   2.71223727e-01 ...,  -2.32586716e-01
   -3.28692755e-01   2.91397629e-01]
 [  5.83283712e-02   1.45434381e-01  -1.41279523e-03 ...,  -2.22437426e-01
    1.63214041e+00   1.14420025e-01]
 [ -5.99308774e-02   2.65011143e-01   4.69795604e-01 ...,   2.39100215e-01
   -2.97707327e-01   9.54164309e-01]
 ..., 
 [ -1.84176187e-01  -2.38508536e-01  -3.86774760e-01 ...,   9.14501082e-02
   -5.92462566e-01  -3.31895459e-01]
 [ -2.74121272e-01  -1.77069433e-01  -1.74760711e-01 ...,  -1.15891144e-01
   -1.37851110e-01  -3.54125400e-01]
 [  3.84633027e-02   8.05515946e-02  -4.30989509e-02 ...,   5.20356935e-02
    2.91061211e+00  -8.44932415e-02]]
Progress: 81.5% ... Training loss: 0.066 ... Validation loss: 0.148[[-0.16394936]
 [-0.95038285]
 [-1.1957168 ]
 [-0.76831903]
 [-0.06201557]
 [ 2.65141673]
 [-0.05062076]
 [-1.10661332]
 [-0.53351893]
 [ 1.04011726]
 [-0.09679551]
 [ 0.14045884]
 [-0.10157525]
 [-1.01345692]
 [-0.30331868]
 [ 0.8628304 ]
 [-0.84006124]
 [-0.79875841]
 [-0.62392254]
 [ 0.14026701]
 [-0.35355549]
 [ 4.49266009]
 [-0.95017951]
 [-1.65418024]
 [ 0.38024109]
 [-0.30683437]
 [ 4.31853925]
 [-1.9314174 ]]
[[ -1.91255292e-02  -3.04951837e-01   2.72160234e-01 ...,  -2.32253869e-01
   -3.32930934e-01   2.93190780e-01]
 [  5.83973914e-02   1.45856401e-01  -9.36417564e-04 ...,  -2.22304949e-01
    1.63109251e+00   1.15254001e-01]
 [ -5.97659129e-02   2.66107769e-01   4.71373537e-01 ...,   2.39459549e-01
   -3.03738484e-01   9.58187202e-01]
 ..., 
 [ -1.84102097e-01  -2.38094019e-01  -3.86274461e-01 ...,   9.15897004e-02
   -5.94141460e-01  -3.31210292e-01]
 [ -2.74098239e-01  -1.76973121e-01  -1.74693115e-01 ...,  -1.15852496e-01
   -1.38459965e-01  -3.54122620e-01]
 [  3.85497333e-02   8.10478323e-02  -4.26237928e-02 ...,   5.21831491e-02
    2.91033339e+00  -8.37592133e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.16263207]
 [-0.94984012]
 [-1.19618381]
 [-0.76623976]
 [-0.06024782]
 [ 2.65159971]
 [-0.04919507]
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 [ 1.04056596]
 [-0.09567477]
 [ 0.14199469]
 [-0.09931401]
 [-1.01313995]
 [-0.30282028]
 [ 0.86502288]
 [-0.83946248]
 [-0.79866125]
 [-0.62384394]
 [ 0.14177627]
 [-0.35237105]
 [ 4.49349006]
 [-0.94874931]
 [-1.65144315]
 [ 0.38104392]
 [-0.30534642]
 [ 4.32046063]
 [-1.93133699]]
[[ -1.92236717e-02  -3.05429646e-01   2.71538981e-01 ...,  -2.32422376e-01
   -3.30749306e-01   2.92900618e-01]
 [  5.83952053e-02   1.45845620e-01  -9.40588921e-04 ...,  -2.22308719e-01
    1.63110576e+00   1.15249107e-01]
 [ -5.94902693e-02   2.67548761e-01   4.72563743e-01 ...,   2.39969794e-01
   -3.04867796e-01   9.59613409e-01]
 ..., 
 [ -1.84227775e-01  -2.38776689e-01  -3.86976899e-01 ...,   9.13720555e-02
   -5.92140673e-01  -3.32151402e-01]
 [ -2.74147625e-01  -1.77249603e-01  -1.74976696e-01 ...,  -1.15942213e-01
   -1.37416804e-01  -3.54655343e-01]
 [  3.85083512e-02   8.07882911e-02  -4.28019497e-02 ...,   5.21052194e-02
    2.91047326e+00  -8.42814429e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16112859]
 [-0.94899018]
 [-1.19542961]
 [-0.76516737]
 [-0.0589604 ]
 [ 2.65200492]
 [-0.04787915]
 [-1.10259887]
 [-0.53185321]
 [ 1.0415832 ]
 [-0.09453615]
 [ 0.14316254]
 [-0.09805794]
 [-1.01214007]
 [-0.30157187]
 [ 0.86648146]
 [-0.8384722 ]
 [-0.79711828]
 [-0.62258102]
 [ 0.14308732]
 [-0.35094937]
 [ 4.49436033]
 [-0.94764745]
 [-1.65020688]
 [ 0.38217115]
 [-0.30426005]
 [ 4.32214442]
 [-1.93135203]]
[[ -1.93135135e-02  -3.05901391e-01   2.71026461e-01 ...,  -2.32574275e-01
   -3.28537020e-01   2.91884508e-01]
 [  5.83552059e-02   1.45603044e-01  -1.25887278e-03 ...,  -2.22386900e-01
    1.63192338e+00   1.14762383e-01]
 [ -5.94712577e-02   2.67664912e-01   4.72884258e-01 ...,   2.40032398e-01
   -3.00731989e-01   9.59717018e-01]
 ..., 
 [ -1.84339220e-01  -2.39413570e-01  -3.87585182e-01 ...,   9.11720163e-02
   -5.90540204e-01  -3.33222793e-01]
 [ -2.74211228e-01  -1.77624172e-01  -1.75430912e-01 ...,  -1.16042365e-01
   -1.36814848e-01  -3.55324856e-01]
 [  3.85464630e-02   8.09599261e-02  -4.25573157e-02 ...,   5.21613420e-02
    2.91033555e+00  -8.37722548e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.15998583]
 [-0.94796904]
 [-1.19356506]
 [-0.76469184]
 [-0.05800569]
 [ 2.65169362]
 [-0.04717342]
 [-1.10226434]
 [-0.52968787]
 [ 1.04322174]
 [-0.09389356]
 [ 0.14408927]
 [-0.09751972]
 [-1.0115052 ]
 [-0.30013526]
 [ 0.86872628]
 [-0.83721394]
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 [-0.62051296]
 [ 0.14426992]
 [-0.34937586]
 [ 4.49427015]
 [-0.94827644]
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 [ 0.38353825]
 [-0.30365897]
 [ 4.32379435]
 [-1.93105864]]
[[ -1.93013953e-02  -3.05840644e-01   2.71099647e-01 ...,  -2.32552569e-01
   -3.26851529e-01   2.91715383e-01]
 [  5.83465690e-02   1.45573381e-01  -1.45896343e-03 ...,  -2.22407270e-01
    1.63304878e+00   1.14559237e-01]
 [ -5.95237315e-02   2.67397194e-01   4.73079169e-01 ...,   2.39932405e-01
   -2.96741498e-01   9.59495384e-01]
 ..., 
 [ -1.84285759e-01  -2.39124758e-01  -3.87193747e-01 ...,   9.12750451e-02
   -5.90606493e-01  -3.32539172e-01]
 [ -2.74440414e-01  -1.78925262e-01  -1.76964127e-01 ...,  -1.16463314e-01
   -1.33257062e-01  -3.57689846e-01]
 [  3.85858405e-02   8.11929125e-02  -4.21431076e-02 ...,   5.22392360e-02
    2.91023725e+00  -8.32525285e-02]]
Progress: 81.5% ... Training loss: 0.062 ... Validation loss: 0.142[[-0.16336526]
 [-0.9507256 ]
 [-1.19673069]
 [-0.7673782 ]
 [-0.06076119]
 [ 2.65136539]
 [-0.04941211]
 [-1.10635064]
 [-0.53167654]
 [ 1.04085956]
 [-0.09702156]
 [ 0.14083388]
 [-0.10116126]
 [-1.01258897]
 [-0.30309098]
 [ 0.86501021]
 [-0.84113435]
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 [-0.62326239]
 [ 0.14183362]
 [-0.35263012]
 [ 4.49480355]
 [-0.9506704 ]
 [-1.65419179]
 [ 0.38192436]
 [-0.30605103]
 [ 4.317561  ]
 [-1.9319854 ]]
[[ -1.91045999e-02  -3.04682944e-01   2.72140580e-01 ...,  -2.32190971e-01
   -3.26433485e-01   2.92702422e-01]
 [  5.83664106e-02   1.45691913e-01  -1.33429805e-03 ...,  -2.22372052e-01
    1.63295255e+00   1.14753728e-01]
 [ -5.97029618e-02   2.66293141e-01   4.72021215e-01 ...,   2.39600508e-01
   -2.93300882e-01   9.58546351e-01]
 ..., 
 [ -1.84246190e-01  -2.38915775e-01  -3.87017425e-01 ...,   9.13502630e-02
   -5.90763348e-01  -3.32416944e-01]
 [ -2.74533296e-01  -1.79457935e-01  -1.77438413e-01 ...,  -1.16631022e-01
   -1.32120610e-01  -3.58360113e-01]
 [  3.88225361e-02   8.25741381e-02  -4.11595723e-02 ...,   5.26759048e-02
    2.90983937e+00  -8.13633001e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.16161567]
 [-0.94902366]
 [-1.19512395]
 [-0.76496001]
 [-0.0585778 ]
 [ 2.65028692]
 [-0.04828927]
 [-1.10427943]
 [-0.52987553]
 [ 1.04225099]
 [-0.09534915]
 [ 0.1424503 ]
 [-0.09987516]
 [-1.01243517]
 [-0.3013786 ]
 [ 0.86640954]
 [-0.83897477]
 [-0.79686495]
 [-0.62131149]
 [ 0.1433546 ]
 [-0.35086113]
 [ 4.49372887]
 [-0.94967679]
 [-1.65166622]
 [ 0.382865  ]
 [-0.30460722]
 [ 4.32087057]
 [-1.93163306]]
[[ -1.90115349e-02  -3.04125950e-01   2.72901878e-01 ...,  -2.32013833e-01
   -3.27425809e-01   2.93629483e-01]
 [  5.83436384e-02   1.45565668e-01  -1.34077831e-03 ...,  -2.22413373e-01
    1.63295347e+00   1.14606254e-01]
 [ -5.96080138e-02   2.66829015e-01   4.72603061e-01 ...,   2.39783117e-01
   -2.95886306e-01   9.58840833e-01]
 ..., 
 [ -1.84237539e-01  -2.38874895e-01  -3.86993772e-01 ...,   9.13663324e-02
   -5.90615375e-01  -3.32279194e-01]
 [ -2.74581374e-01  -1.79737653e-01  -1.77856514e-01 ...,  -1.16713461e-01
   -1.31511563e-01  -3.59028311e-01]
 [  3.87531554e-02   8.21864718e-02  -4.15053478e-02 ...,   5.25439223e-02
    2.90988250e+00  -8.17756332e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16626861]
 [-0.95296996]
 [-1.19880783]
 [-0.76867154]
 [-0.06198528]
 [ 2.64680277]
 [-0.05213875]
 [-1.10613868]
 [-0.53464298]
 [ 1.03997288]
 [-0.09875586]
 [ 0.13896874]
 [-0.10391369]
 [-1.01647986]
 [-0.30550778]
 [ 0.86234973]
 [-0.84353902]
 [-0.80020589]
 [-0.62477607]
 [ 0.13935772]
 [-0.35431006]
 [ 4.492841  ]
 [-0.9535069 ]
 [-1.65414505]
 [ 0.37926407]
 [-0.30842128]
 [ 4.31455415]
 [-1.93464645]]
[[ -1.88322593e-02  -3.03136641e-01   2.73943657e-01 ...,  -2.31685602e-01
   -3.30597276e-01   2.95385910e-01]
 [  5.83436384e-02   1.45565668e-01  -1.34077831e-03 ...,  -2.22413373e-01
    1.63295347e+00   1.14606254e-01]
 [ -5.92932796e-02   2.68614551e-01   4.75331531e-01 ...,   2.40365171e-01
   -3.01788468e-01   9.62548981e-01]
 ..., 
 [ -1.84167668e-01  -2.38451883e-01  -3.86445326e-01 ...,   9.15005969e-02
   -5.92023698e-01  -3.31568784e-01]
 [ -2.74567382e-01  -1.79676656e-01  -1.77771539e-01 ...,  -1.16691734e-01
   -1.31740090e-01  -3.59140708e-01]
 [  3.88509885e-02   8.27438398e-02  -4.09385206e-02 ...,   5.27286240e-02
    2.90969402e+00  -8.08049118e-02]]
Progress: 81.5% ... Training loss: 0.063 ... Validation loss: 0.136[[-0.16112766]
 [-0.94862073]
 [-1.19400312]
 [-0.76489093]
 [-0.05803816]
 [ 2.64831913]
 [-0.048106  ]
 [-1.10290662]
 [-0.52965007]
 [ 1.04389293]
 [-0.09472783]
 [ 0.14327609]
 [-0.0993716 ]
 [-1.01350142]
 [-0.30054323]
 [ 0.86763235]
 [-0.83813356]
 [-0.79521714]
 [-0.62014561]
 [ 0.14397496]
 [-0.34976517]
 [ 4.49434379]
 [-0.9502577 ]
 [-1.6490123 ]
 [ 0.38262807]
 [-0.30422376]
 [ 4.32256699]
 [-1.9322614 ]]
[[ -1.89994937e-02  -3.04040432e-01   2.72901516e-01 ...,  -2.31983288e-01
   -3.28216507e-01   2.94166197e-01]
 [  5.83501032e-02   1.45595837e-01  -1.46483484e-03 ...,  -2.22401055e-01
    1.63304916e+00   1.14605721e-01]
 [ -5.93879843e-02   2.68039534e-01   4.74313848e-01 ...,   2.40181797e-01
   -3.00357654e-01   9.60359561e-01]
 ..., 
 [ -1.84210221e-01  -2.38701223e-01  -3.86900417e-01 ...,   9.14270682e-02
   -5.91315218e-01  -3.32037910e-01]
 [ -2.74674338e-01  -1.80271901e-01  -1.78306170e-01 ...,  -1.16887099e-01
   -1.30556298e-01  -3.59975515e-01]
 [  3.88569394e-02   8.27717351e-02  -4.10174041e-02 ...,   5.27430754e-02
    2.90963165e+00  -8.09206497e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16360642]
 [-0.95024907]
 [-1.19647801]
 [-0.76589841]
 [-0.05938652]
 [ 2.64751674]
 [-0.05012422]
 [-1.10539894]
 [-0.5316201 ]
 [ 1.04034408]
 [-0.09693067]
 [ 0.14064059]
 [-0.10139054]
 [-1.01480269]
 [-0.30276814]
 [ 0.86415701]
 [-0.84070881]
 [-0.799267  ]
 [-0.6225367 ]
 [ 0.14208755]
 [-0.35270362]
 [ 4.49373514]
 [-0.9510814 ]
 [-1.65206996]
 [ 0.38076058]
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 [ 4.31936715]
 [-1.93295377]]
[[ -1.89828475e-02  -3.03997309e-01   2.73199858e-01 ...,  -2.31960093e-01
   -3.29112423e-01   2.94574551e-01]
 [  5.83426635e-02   1.45546621e-01  -1.43352724e-03 ...,  -2.22415133e-01
    1.63301502e+00   1.14578378e-01]
 [ -5.94607595e-02   2.67577000e-01   4.73483108e-01 ...,   2.40067051e-01
   -3.00945838e-01   9.59828851e-01]
 ..., 
 [ -1.84118583e-01  -2.38183617e-01  -3.86381123e-01 ...,   9.15910898e-02
   -5.93078477e-01  -3.31366813e-01]
 [ -2.74578682e-01  -1.79735495e-01  -1.77682839e-01 ...,  -1.16734695e-01
   -1.30963238e-01  -3.59698548e-01]
 [  3.88789517e-02   8.29142707e-02  -4.06645537e-02 ...,   5.27824398e-02
    2.90964979e+00  -8.05124929e-02]]
Progress: 81.5% ... Training loss: 0.060 ... Validation loss: 0.136[[-0.16549891]
 [-0.95162639]
 [-1.19594787]
 [-0.7684655 ]
 [-0.06196436]
 [ 2.64885755]
 [-0.05138133]
 [-1.10890346]
 [-0.53145847]
 [ 1.0399291 ]
 [-0.09852039]
 [ 0.13887193]
 [-0.10323905]
 [-1.01315664]
 [-0.30420116]
 [ 0.86203453]
 [-0.84191111]
 [-0.79931678]
 [-0.62344486]
 [ 0.13974599]
 [-0.35430502]
 [ 4.49267374]
 [-0.95227426]
 [-1.65560565]
 [ 0.38021928]
 [-0.30722813]
 [ 4.31603553]
 [-1.93196309]]
[[ -1.90115059e-02  -3.04197382e-01   2.72785939e-01 ...,  -2.32009733e-01
   -3.28483713e-01   2.93643598e-01]
 [  5.82474964e-02   1.44991955e-01  -2.25021686e-03 ...,  -2.22583080e-01
    1.63407630e+00   1.13221332e-01]
 [ -5.98334882e-02   2.65408249e-01   4.71564475e-01 ...,   2.39426006e-01
   -2.96111236e-01   9.56835872e-01]
 ..., 
 [ -1.84095899e-01  -2.38048274e-01  -3.86378724e-01 ...,   9.16300378e-02
   -5.92181042e-01  -3.31249050e-01]
 [ -2.74616459e-01  -1.79971686e-01  -1.77788566e-01 ...,  -1.16810599e-01
   -1.30634655e-01  -3.60083013e-01]
 [  3.89461338e-02   8.33340112e-02  -4.03627583e-02 ...,   5.29111245e-02
    2.90955621e+00  -8.00002428e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.134[[-0.16633078]
 [-0.95261274]
 [-1.1980296 ]
 [-0.76876647]
 [-0.06189798]
 [ 2.64811645]
 [-0.05235749]
 [-1.10810193]
 [-0.53339021]
 [ 1.03828666]
 [-0.09930998]
 [ 0.13803959]
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 [ 0.86106496]
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 [ 0.13911839]
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 [ 4.49181693]
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 [ 0.37896151]
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 [ 4.31419852]
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[[ -1.91135222e-02  -3.04744974e-01   2.72211480e-01 ...,  -2.32187961e-01
   -3.28242630e-01   2.92977453e-01]
 [  5.82474534e-02   1.44984944e-01  -2.24530377e-03 ...,  -2.22584823e-01
    1.63406167e+00   1.13193169e-01]
 [ -5.95705227e-02   2.66902273e-01   4.73110184e-01 ...,   2.39930700e-01
   -2.97593751e-01   9.59183554e-01]
 ..., 
 [ -1.84082049e-01  -2.37979493e-01  -3.86305828e-01 ...,   9.16549121e-02
   -5.92473519e-01  -3.30991907e-01]
 [ -2.74443017e-01  -1.79058449e-01  -1.76638420e-01 ...,  -1.16508228e-01
   -1.32906500e-01  -3.58712608e-01]
 [  3.88795737e-02   8.29729031e-02  -4.07265872e-02 ...,   5.27911126e-02
    2.90960846e+00  -8.07181133e-02]]
Progress: 81.5% ... Training loss: 0.062 ... Validation loss: 0.135[[-0.15771442]
 [-0.94461909]
 [-1.19148408]
 [-0.76219065]
 [-0.05464724]
 [ 2.65359473]
 [-0.04416927]
 [-1.10162972]
 [-0.52493237]
 [ 1.04380324]
 [-0.0911832 ]
 [ 0.14626559]
 [-0.09523296]
 [-1.00774434]
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 [ 0.87014372]
 [-0.83505061]
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 [ 0.14648717]
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 [ 4.49377796]
 [-0.94583296]
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 [ 0.38650488]
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 [ 4.32904211]
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[[-0.01960109 -0.30743603  0.26962505 ..., -0.23305886 -0.32261618
   0.2892948 ]
 [ 0.05810255  0.14418838 -0.00313602 ..., -0.22285274  1.63495429
   0.11194671]
 [-0.05978999  0.26570409  0.47161521 ...,  0.23954684 -0.29350235
   0.95531741]
 ..., 
 [-0.18423567 -0.23879586 -0.38682454 ...,  0.09137336 -0.59029518
  -0.33216763]
 [-0.27457096 -0.17974595 -0.17718313 ..., -0.11672678 -0.13192363
  -0.35917957]
 [ 0.0387621   0.08232225 -0.04135099 ...,  0.05257737  2.90994825
  -0.08209693]]
Progress: 81.5% ... Training loss: 0.068 ... Validation loss: 0.147[[-0.16615526]
 [-0.95049073]
 [-1.19688154]
 [-0.76905587]
 [-0.06128775]
 [ 2.65044262]
 [-0.05107041]
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 [ 1.03885528]
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 [ 0.13891201]
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 [ 0.13959497]
 [-0.35450988]
 [ 4.49286095]
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 [ 0.38027441]
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 [ 4.3168082 ]
 [-1.93287585]]
[[ -1.92930811e-02  -3.05679725e-01   2.71539800e-01 ...,  -2.32500832e-01
   -3.26561272e-01   2.92020338e-01]
 [  5.81519378e-02   1.44465343e-01  -2.78484594e-03 ...,  -2.22764411e-01
    1.63465715e+00   1.12401574e-01]
 [ -5.98033002e-02   2.65643939e-01   4.72024776e-01 ...,   2.39530647e-01
   -2.97853754e-01   9.57496460e-01]
 ..., 
 [ -1.84098037e-01  -2.38026074e-01  -3.86096826e-01 ...,   9.16346783e-02
   -5.93133996e-01  -3.31103656e-01]
 [ -2.74477786e-01  -1.79239261e-01  -1.76834821e-01 ...,  -1.16564373e-01
   -1.32595518e-01  -3.59124638e-01]
 [  3.88600117e-02   8.29085111e-02  -4.07357834e-02 ...,   5.27620658e-02
    2.90984745e+00  -8.13130412e-02]]
Progress: 81.5% ... Training loss: 0.061 ... Validation loss: 0.135[[-0.16055629]
 [-0.94504232]
 [-1.19117295]
 [-0.76634914]
 [-0.0573755 ]
 [ 2.65476406]
 [-0.04625281]
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 [-0.52521362]
 [ 1.0422939 ]
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 [ 0.14381823]
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 [ 0.86701653]
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 [ 0.14460161]
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 [ 0.38531713]
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 [ 4.32577017]
 [-1.92920665]]
[[-0.01967361 -0.30778036  0.26917684 ..., -0.23318226 -0.32145911
   0.28850249]
 [ 0.05810281  0.14417053 -0.00331597 ..., -0.22286064  1.63628061
   0.11160183]
 [-0.06021867  0.26331572  0.46931277 ...,  0.23878177 -0.29096257
   0.952457  ]
 ..., 
 [-0.18405239 -0.2377888  -0.38599514 ...,  0.09171833 -0.59368754
  -0.331087  ]
 [-0.27450737 -0.17939289 -0.17694737 ..., -0.11661154 -0.13196183
  -0.35921937]
 [ 0.03868166  0.08192169 -0.04160882 ...,  0.05242634  2.91001582
  -0.0827949 ]]
Progress: 81.6% ... Training loss: 0.065 ... Validation loss: 0.139[[-0.16994076]
 [-0.95397245]
 [-1.20020561]
 [-0.77296851]
 [-0.06438408]
 [ 2.64899548]
 [-0.05441525]
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 [ 1.03680604]
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 [ 0.13562938]
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 [ 0.85736175]
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 [ 0.37777311]
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 [ 4.3111594 ]
 [-1.93444691]]
[[ -1.91693209e-02  -3.04905466e-01   2.72149929e-01 ...,  -2.32258052e-01
   -3.26714038e-01   2.93503679e-01]
 [  5.82252603e-02   1.44855615e-01  -2.47415241e-03 ...,  -2.22633408e-01
    1.63594438e+00   1.12941153e-01]
 [ -5.97048025e-02   2.66225048e-01   4.72555465e-01 ...,   2.39748747e-01
   -2.97023394e-01   9.58055779e-01]
 ..., 
 [ -1.84027528e-01  -2.37657637e-01  -3.85888946e-01 ...,   9.17630764e-02
   -5.94455705e-01  -3.30784094e-01]
 [ -2.74425265e-01  -1.78935932e-01  -1.76539858e-01 ...,  -1.16470084e-01
   -1.33935526e-01  -3.58569117e-01]
 [  3.87604907e-02   8.23961995e-02  -4.11423249e-02 ...,   5.25812252e-02
    2.91015599e+00  -8.19468389e-02]]
Progress: 81.6% ... Training loss: 0.067 ... Validation loss: 0.137[[-0.16254847]
 [-0.94783736]
 [-1.19536437]
 [-0.76551979]
 [-0.05796118]
 [ 2.65040585]
 [-0.04824521]
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 [-0.52931345]
 [ 1.0418347 ]
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 [ 0.14187657]
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 [-0.30099047]
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 [ 4.49367319]
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 [ 4.32348412]
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[[ -1.93473093e-02  -3.05838623e-01   2.71291753e-01 ...,  -2.32557192e-01
   -3.25114772e-01   2.92396955e-01]
 [  5.81736030e-02   1.44564217e-01  -2.77338765e-03 ...,  -2.22722796e-01
    1.63635215e+00   1.12443007e-01]
 [ -5.96113507e-02   2.66712659e-01   4.72462997e-01 ...,   2.39927523e-01
   -2.96956416e-01   9.57252969e-01]
 ..., 
 [ -1.84142530e-01  -2.38292122e-01  -3.86363634e-01 ...,   9.15527669e-02
   -5.92258880e-01  -3.31687361e-01]
 [ -2.74542607e-01  -1.79565032e-01  -1.77088033e-01 ...,  -1.16663477e-01
   -1.33494824e-01  -3.59244954e-01]
 [  3.87080762e-02   8.21044445e-02  -4.14373013e-02 ...,   5.24924654e-02
    2.91019746e+00  -8.20689147e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16616413]
 [-0.95179728]
 [-1.19876602]
 [-0.76932108]
 [-0.06214835]
 [ 2.65151152]
 [-0.05148985]
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 [ 1.03844472]
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 [ 0.13770039]
 [-0.10249044]
 [-1.01078253]
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 [ 0.14027063]
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 [ 4.49367619]
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 [ 0.38035113]
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 [ 4.31712662]
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[[ -1.94165414e-02  -3.06287101e-01   2.71018670e-01 ...,  -2.32680480e-01
   -3.24441967e-01   2.91507946e-01]
 [  5.81720034e-02   1.44555169e-01  -2.77731313e-03 ...,  -2.22725745e-01
    1.63635465e+00   1.12435765e-01]
 [ -5.98314990e-02   2.65431452e-01   4.71302507e-01 ...,   2.39529164e-01
   -2.94059520e-01   9.55320901e-01]
 ..., 
 [ -1.83945368e-01  -2.37196197e-01  -3.85653836e-01 ...,   9.19111634e-02
   -5.94512273e-01  -3.30679398e-01]
 [ -2.74534625e-01  -1.79541192e-01  -1.76929329e-01 ...,  -1.16650530e-01
   -1.33196444e-01  -3.59540710e-01]
 [  3.88229069e-02   8.27716289e-02  -4.07724538e-02 ...,   5.26990195e-02
    2.91015919e+00  -8.11410871e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.136[[-0.16276741]
 [-0.95000282]
 [-1.19626608]
 [-0.76627425]
 [-0.05969146]
 [ 2.65211978]
 [-0.04938839]
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 [ 1.03967272]
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 [ 0.14035269]
 [-0.09958342]
 [-1.00987616]
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 [ 0.86237845]
 [-0.84026534]
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 [-0.62400452]
 [ 0.142696  ]
 [-0.35272414]
 [ 4.49367474]
 [-0.94632534]
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 [ 0.38191343]
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 [ 4.32333982]
 [-1.93093752]]
[[ -1.96196381e-02  -3.07362022e-01   2.69841474e-01 ...,  -2.33040009e-01
   -3.24142634e-01   2.90501519e-01]
 [  5.81789894e-02   1.44595496e-01  -2.73727939e-03 ...,  -2.22713687e-01
    1.63629944e+00   1.12511761e-01]
 [ -5.96308608e-02   2.66450375e-01   4.72118038e-01 ...,   2.39883205e-01
   -2.96693301e-01   9.55626383e-01]
 ..., 
 [ -1.83931381e-01  -2.37100476e-01  -3.85773001e-01 ...,   9.19366619e-02
   -5.94236586e-01  -3.30538304e-01]
 [ -2.74516296e-01  -1.79435024e-01  -1.76758030e-01 ...,  -1.16612036e-01
   -1.33667670e-01  -3.59297882e-01]
 [  3.87108982e-02   8.21587488e-02  -4.14757079e-02 ...,   5.25015376e-02
    2.91026275e+00  -8.17324311e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16252873]
 [-0.94952562]
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 [-0.76647111]
 [-0.05993705]
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 [ 0.14064122]
 [-0.10002088]
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 [ 0.86275452]
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 [ 4.49316883]
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 [ 0.3822167 ]
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 [ 4.32299401]
 [-1.93033376]]
[[ -1.95683955e-02  -3.07119304e-01   2.69927319e-01 ...,  -2.32941703e-01
   -3.24222739e-01   2.90957565e-01]
 [  5.82550292e-02   1.45042630e-01  -2.39465589e-03 ...,  -2.22569030e-01
    1.63519117e+00   1.13191955e-01]
 [ -5.96490196e-02   2.66460781e-01   4.72320032e-01 ...,   2.39850807e-01
   -2.95995278e-01   9.55406475e-01]
 ..., 
 [ -1.83975804e-01  -2.37344006e-01  -3.86141337e-01 ...,   9.18542373e-02
   -5.93582685e-01  -3.30896234e-01]
 [ -2.74547455e-01  -1.79596265e-01  -1.76992874e-01 ...,  -1.16655718e-01
   -1.33011696e-01  -3.59606445e-01]
 [  3.87419857e-02   8.22900627e-02  -4.13541910e-02 ...,   5.25550891e-02
    2.91019422e+00  -8.18801486e-02]]
Progress: 81.6% ... Training loss: 0.060 ... Validation loss: 0.137[[-0.16366614]
 [-0.95055151]
 [-1.19912338]
 [-0.76587052]
 [-0.0593299 ]
 [ 2.6489087 ]
 [-0.05032346]
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 [ 1.03820092]
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 [ 0.13984131]
 [-0.09999645]
 [-1.01225123]
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 [ 0.86142403]
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 [ 4.49311539]
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 [ 4.32212318]
 [-1.93180073]]
[[ -1.94723143e-02  -3.06554949e-01   2.70828923e-01 ...,  -2.32760149e-01
   -3.25532680e-01   2.92228144e-01]
 [  5.81464032e-02   1.44413357e-01  -2.78040991e-03 ...,  -2.22767710e-01
    1.63579744e+00   1.12518104e-01]
 [ -5.92302112e-02   2.68794871e-01   4.74696945e-01 ...,   2.40634697e-01
   -2.99303991e-01   9.59342876e-01]
 ..., 
 [ -1.83900277e-01  -2.36930755e-01  -3.85768168e-01 ...,   9.19933689e-02
   -5.95299038e-01  -3.30135059e-01]
 [ -2.74668237e-01  -1.80283631e-01  -1.77417764e-01 ...,  -1.16878096e-01
   -1.32079393e-01  -3.60405537e-01]
 [  3.86727086e-02   8.18847972e-02  -4.16696253e-02 ...,   5.24260529e-02
    2.91016537e+00  -8.24502340e-02]]
Progress: 81.6% ... Training loss: 0.060 ... Validation loss: 0.138[[-0.16249039]
 [-0.95033059]
 [-1.19884345]
 [-0.76450866]
 [-0.0589567 ]
 [ 2.64893259]
 [-0.04966311]
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 [ 0.14016447]
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 [ 0.38065422]
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[[-0.01939426 -0.30609506  0.27097101 ..., -0.23263956 -0.32629809
   0.29297904]
 [ 0.05810284  0.14416947 -0.00301936 ..., -0.22284877  1.63609862
   0.11198729]
 [-0.05917642  0.26909196  0.47474249 ...,  0.24072599 -0.29919396
   0.95929235]
 ..., 
 [-0.1840067  -0.23754056 -0.38637058 ...,  0.09180737 -0.59429155
  -0.33090849]
 [-0.2745669  -0.17970976 -0.1772481  ..., -0.11671372 -0.13236118
  -0.3594857 ]
 [ 0.03875614  0.08235812 -0.0410933  ...,  0.05257886  2.90994324
  -0.08194965]]
Progress: 81.6% ... Training loss: 0.060 ... Validation loss: 0.139[[-0.16364588]
 [-0.95209905]
 [-1.19972373]
 [-0.76510695]
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 [ 2.64826427]
 [-0.05118639]
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[[ -1.93066606e-02  -3.05596005e-01   2.71291544e-01 ...,  -2.32485279e-01
   -3.27104326e-01   2.93479879e-01]
 [  5.81336027e-02   1.44340968e-01  -2.81498207e-03 ...,  -2.22789819e-01
    1.63603992e+00   1.12136466e-01]
 [ -5.90627349e-02   2.69748873e-01   4.75461528e-01 ...,   2.40950200e-01
   -3.00749493e-01   9.60560966e-01]
 ..., 
 [ -1.83977652e-01  -2.37399438e-01  -3.86348288e-01 ...,   9.18695646e-02
   -5.94900408e-01  -3.30796659e-01]
 [ -2.74428905e-01  -1.78940323e-01  -1.76427067e-01 ...,  -1.16466953e-01
   -1.33627639e-01  -3.58465707e-01]
 [  3.88090863e-02   8.26719767e-02  -4.09033148e-02 ...,   5.26757340e-02
    2.90996712e+00  -8.12618227e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.1630292 ]
 [-0.95232571]
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[[ -1.93141345e-02  -3.05661701e-01   2.70977044e-01 ...,  -2.32488679e-01
   -3.26966121e-01   2.92959180e-01]
 [  5.81427371e-02   1.44397234e-01  -2.76329673e-03 ...,  -2.22774804e-01
    1.63597657e+00   1.12240690e-01]
 [ -5.88856986e-02   2.70749101e-01   4.76650468e-01 ...,   2.41277471e-01
   -3.00752417e-01   9.61765975e-01]
 ..., 
 [ -1.83994486e-01  -2.37495032e-01  -3.86445449e-01 ...,   9.18402682e-02
   -5.94500666e-01  -3.30909210e-01]
 [ -2.74387614e-01  -1.78694216e-01  -1.76205735e-01 ...,  -1.16393094e-01
   -1.34352561e-01  -3.58192978e-01]
 [  3.88767773e-02   8.30567903e-02  -4.03159762e-02 ...,   5.27995261e-02
    2.90972669e+00  -8.01302377e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.15966562]
 [-0.94850175]
 [-1.19470016]
 [-0.76296102]
 [-0.0566359 ]
 [ 2.64917196]
 [-0.04881098]
 [-1.10250701]
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 [ 1.04290556]
 [-0.09426647]
 [ 0.14237243]
 [-0.10005057]
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 [ 0.86518153]
 [-0.83752015]
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 [ 0.14501018]
 [-0.3509122 ]
 [ 4.49408126]
 [-0.94519633]
 [-1.64647265]
 [ 0.38210622]
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 [ 4.32696315]
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[[ -1.94499380e-02  -3.06432606e-01   2.70123954e-01 ...,  -2.32743449e-01
   -3.25833837e-01   2.91979314e-01]
 [  5.81933404e-02   1.44689536e-01  -2.76627799e-03 ...,  -2.22683288e-01
    1.63598351e+00   1.12671052e-01]
 [ -5.92371938e-02   2.68675861e-01   4.74276860e-01 ...,   2.40634896e-01
   -2.98486879e-01   9.58060404e-01]
 ..., 
 [ -1.83989892e-01  -2.37450842e-01  -3.86765604e-01 ...,   9.18462854e-02
   -5.93681515e-01  -3.30876236e-01]
 [ -2.74458096e-01  -1.79105549e-01  -1.76672230e-01 ...,  -1.16523128e-01
   -1.33001581e-01  -3.58758332e-01]
 [  3.89331064e-02   8.33816076e-02  -4.01224446e-02 ...,   5.29062563e-02
    2.90968219e+00  -7.99537755e-02]]
Progress: 81.6% ... Training loss: 0.062 ... Validation loss: 0.140[[-0.16083801]
 [-0.94974863]
 [-1.1958262 ]
 [-0.76404762]
 [-0.05821223]
 [ 2.65085878]
 [-0.04996973]
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 [-0.53010293]
 [ 1.04114816]
 [-0.09460703]
 [ 0.14157558]
 [-0.10182358]
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 [-0.8386998 ]
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 [ 0.1435669 ]
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 [ 4.49375759]
 [-0.94690373]
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 [ 0.38141565]
 [-0.30558656]
 [ 4.32541782]
 [-1.93299309]]
[[ -1.95161697e-02  -3.06895948e-01   2.69694162e-01 ...,  -2.32875360e-01
   -3.25659415e-01   2.91531614e-01]
 [  5.82052579e-02   1.44747792e-01  -2.68016905e-03 ...,  -2.22657153e-01
    1.63634015e+00   1.12698930e-01]
 [ -5.92664213e-02   2.68485015e-01   4.74596890e-01 ...,   2.40585496e-01
   -2.99550818e-01   9.58184044e-01]
 ..., 
 [ -1.83972866e-01  -2.37353072e-01  -3.86655049e-01 ...,   9.18783221e-02
   -5.94084443e-01  -3.30661852e-01]
 [ -2.74355419e-01  -1.78584862e-01  -1.75916070e-01 ...,  -1.16344976e-01
   -1.35422959e-01  -3.57889445e-01]
 [  3.89149982e-02   8.32685497e-02  -4.03826208e-02 ...,   5.28703365e-02
    2.90983848e+00  -8.02774569e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16209396]
 [-0.95056859]
 [-1.19744837]
 [-0.76478915]
 [-0.05962609]
 [ 2.65176937]
 [-0.05089033]
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 [ 1.03890373]
 [-0.09658296]
 [ 0.14064872]
 [-0.10243661]
 [-1.01404831]
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 [ 0.86350875]
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 [-0.62386   ]
 [ 0.14309459]
 [-0.35352494]
 [ 4.49328821]
 [-0.94752045]
 [-1.64851408]
 [ 0.3808761 ]
 [-0.30658465]
 [ 4.32438576]
 [-1.93373275]]
[[ -1.95838403e-02  -3.07255428e-01   2.69328587e-01 ...,  -2.33003107e-01
   -3.26687500e-01   2.91254773e-01]
 [  5.82887016e-02   1.45235856e-01  -2.23656590e-03 ...,  -2.22501790e-01
    1.63521900e+00   1.13450667e-01]
 [ -5.92025597e-02   2.68819285e-01   4.75191708e-01 ...,   2.40722870e-01
   -3.02056739e-01   9.59524629e-01]
 ..., 
 [ -1.83857811e-01  -2.36701301e-01  -3.85878938e-01 ...,   9.20871915e-02
   -5.96393699e-01  -3.29787851e-01]
 [ -2.74360144e-01  -1.78622839e-01  -1.75937054e-01 ...,  -1.16351032e-01
   -1.35698927e-01  -3.57857311e-01]
 [  3.87735580e-02   8.24844233e-02  -4.11810489e-02 ...,   5.26134595e-02
    2.91027837e+00  -8.16101934e-02]]
Progress: 81.6% ... Training loss: 0.060 ... Validation loss: 0.138[[-0.16148435]
 [-0.95046694]
 [-1.19657207]
 [-0.76521174]
 [-0.05989918]
 [ 2.6519811 ]
 [-0.05051002]
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 [-0.53092591]
 [ 1.039505  ]
 [-0.09636504]
 [ 0.1406111 ]
 [-0.10221468]
 [-1.01333906]
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 [ 0.86369181]
 [-0.83902009]
 [-0.79876251]
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 [ 0.14306271]
 [-0.35311647]
 [ 4.49336942]
 [-0.94725511]
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 [ 0.38170607]
 [-0.30642929]
 [ 4.32561467]
 [-1.93249576]]
[[ -1.96326213e-02  -3.07511480e-01   2.68603905e-01 ...,  -2.33083999e-01
   -3.27123845e-01   2.90528028e-01]
 [  5.82714798e-02   1.45137225e-01  -2.35557067e-03 ...,  -2.22533118e-01
    1.63546389e+00   1.13278958e-01]
 [ -5.93752334e-02   2.67716176e-01   4.74326806e-01 ...,   2.40400908e-01
   -3.01722928e-01   9.57968769e-01]
 ..., 
 [ -1.83845060e-01  -2.36632769e-01  -3.85826561e-01 ...,   9.21075970e-02
   -5.96223004e-01  -3.29353252e-01]
 [ -2.74426168e-01  -1.79021532e-01  -1.76384996e-01 ...,  -1.16479701e-01
   -1.36027740e-01  -3.58253060e-01]
 [  3.87784630e-02   8.25242181e-02  -4.11362285e-02 ...,   5.26272062e-02
    2.91037944e+00  -8.20032802e-02]]
Progress: 81.6% ... Training loss: 0.060 ... Validation loss: 0.137[[-0.15945003]
 [-0.94961438]
 [-1.19550285]
 [-0.76330559]
 [-0.05875647]
 [ 2.65317021]
 [-0.04913657]
 [-1.10270543]
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 [ 1.03986553]
 [-0.09528526]
 [ 0.14173129]
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 [-1.01226772]
 [-0.30153028]
 [ 0.86475647]
 [-0.83731987]
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 [ 0.14400074]
 [-0.35198861]
 [ 4.4942547 ]
 [-0.94542574]
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 [ 4.32909779]
 [-1.93187432]]
[[ -1.96954019e-02  -3.07859153e-01   2.68219324e-01 ...,  -2.33222739e-01
   -3.27850928e-01   2.89825249e-01]
 [  5.82541505e-02   1.45038633e-01  -2.38707294e-03 ...,  -2.22566365e-01
    1.63551339e+00   1.13196169e-01]
 [ -5.93018493e-02   2.67973348e-01   4.74720568e-01 ...,   2.40515019e-01
   -3.04800855e-01   9.57618680e-01]
 ..., 
 [ -1.83909984e-01  -2.37012861e-01  -3.86127339e-01 ...,   9.19863302e-02
   -5.95356733e-01  -3.29686504e-01]
 [ -2.74378589e-01  -1.78760877e-01  -1.75955838e-01 ...,  -1.16398487e-01
   -1.36529151e-01  -3.57711023e-01]
 [  3.88071849e-02   8.26959893e-02  -4.10138529e-02 ...,   5.26767817e-02
    2.91032057e+00  -8.17572717e-02]]
Progress: 81.6% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16189811]
 [-0.95188898]
 [-1.1969048 ]
 [-0.765311  ]
 [-0.0606654 ]
 [ 2.65110437]
 [-0.05183385]
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 [-0.53315142]
 [ 1.03814143]
 [-0.09731662]
 [ 0.13975718]
 [-0.10271386]
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 [ 0.86266885]
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 [ 4.49326028]
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[[ -1.96361286e-02  -3.07621725e-01   2.68832105e-01 ...,  -2.33111104e-01
   -3.28787881e-01   2.90845830e-01]
 [  5.82647200e-02   1.45117446e-01  -2.11093293e-03 ...,  -2.22549029e-01
    1.63543387e+00   1.13407189e-01]
 [ -5.90838054e-02   2.69270771e-01   4.76285874e-01 ...,   2.40967489e-01
   -3.06518994e-01   9.60488097e-01]
 ..., 
 [ -1.83875210e-01  -2.36800614e-01  -3.85872124e-01 ...,   9.20483149e-02
   -5.95597756e-01  -3.29566041e-01]
 [ -2.74354329e-01  -1.78617839e-01  -1.75835687e-01 ...,  -1.16356874e-01
   -1.36481681e-01  -3.57591038e-01]
 [  3.87887026e-02   8.25384757e-02  -4.11054747e-02 ...,   5.26498111e-02
    2.91034036e+00  -8.14515795e-02]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.138[[-0.16586427]
 [-0.95578748]
 [-1.19941959]
 [-0.76833724]
 [-0.06342658]
 [ 2.64986479]
 [-0.05437548]
 [-1.10682611]
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 [ 1.03696822]
 [-0.10059616]
 [ 0.13619836]
 [-0.10631584]
 [-1.01664538]
 [-0.30732901]
 [ 0.85845307]
 [-0.84288119]
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 [ 0.1380534 ]
 [-0.35765076]
 [ 4.49301367]
 [-0.95041002]
 [-1.65199566]
 [ 0.37795114]
 [-0.31041877]
 [ 4.31791198]
 [-1.93603732]]
[[ -1.94321874e-02  -3.06457080e-01   2.70451549e-01 ...,  -2.32740188e-01
   -3.27610973e-01   2.91761204e-01]
 [  5.82115903e-02   1.44802279e-01  -2.41582232e-03 ...,  -2.22633645e-01
    1.63609346e+00   1.12927014e-01]
 [ -5.91229406e-02   2.68947196e-01   4.76124065e-01 ...,   2.40916151e-01
   -3.02912477e-01   9.60543113e-01]
 ..., 
 [ -1.83802630e-01  -2.36400508e-01  -3.85385595e-01 ...,   9.21825830e-02
   -5.97430561e-01  -3.28906670e-01]
 [ -2.74436069e-01  -1.79074326e-01  -1.76053363e-01 ...,  -1.16518348e-01
   -1.34446982e-01  -3.58549217e-01]
 [  3.88922124e-02   8.31229241e-02  -4.04084802e-02 ...,   5.28345358e-02
    2.91020204e+00  -8.03782470e-02]]
Progress: 81.7% ... Training loss: 0.064 ... Validation loss: 0.138[[-0.15917387]
 [-0.95050777]
 [-1.19356284]
 [-0.76287442]
 [-0.05823075]
 [ 2.65208345]
 [-0.04974865]
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 [ 1.04075061]
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 [ 0.14175353]
 [-0.10111336]
 [-1.01466644]
 [-0.30102128]
 [ 0.86542267]
 [-0.83631039]
 [-0.79662246]
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 [ 0.14373946]
 [-0.35208069]
 [ 4.49375892]
 [-0.94641033]
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 [ 0.38180566]
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 [ 4.32888182]
 [-1.93368774]]
[[ -1.96569138e-02  -3.07704865e-01   2.69322631e-01 ...,  -2.33158337e-01
   -3.25628420e-01   2.89741047e-01]
 [  5.82267804e-02   1.44904244e-01  -2.40780968e-03 ...,  -2.22601899e-01
    1.63588017e+00   1.13122471e-01]
 [ -5.90435424e-02   2.69359075e-01   4.76248368e-01 ...,   2.41078852e-01
   -3.04224901e-01   9.59076840e-01]
 ..., 
 [ -1.83837631e-01  -2.36632318e-01  -3.85818133e-01 ...,   9.21175303e-02
   -5.96714895e-01  -3.29213146e-01]
 [ -2.74483725e-01  -1.79350365e-01  -1.76387844e-01 ...,  -1.16601192e-01
   -1.34754877e-01  -3.58381740e-01]
 [  3.88189713e-02   8.26914006e-02  -4.10699670e-02 ...,   5.26950576e-02
    2.91040339e+00  -8.11141884e-02]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.141[[-0.16442129]
 [-0.95491921]
 [-1.19637448]
 [-0.7677582 ]
 [-0.06182088]
 [ 2.64937597]
 [-0.05411228]
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 [ 1.03903226]
 [-0.09907829]
 [ 0.13795538]
 [-0.10566584]
 [-1.01800261]
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 [ 0.86163475]
 [-0.84162104]
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 [ 0.13959493]
 [-0.35606272]
 [ 4.49344887]
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 [-1.64858044]
 [ 0.37879785]
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 [ 4.31974936]
 [-1.93580415]]
[[ -1.94546471e-02  -3.06591774e-01   2.70301705e-01 ...,  -2.32780604e-01
   -3.25433680e-01   2.91332637e-01]
 [  5.82316906e-02   1.44930021e-01  -2.40094485e-03 ...,  -2.22593873e-01
    1.63585319e+00   1.13128447e-01]
 [ -5.89997483e-02   2.69537627e-01   4.77184393e-01 ...,   2.41158057e-01
   -3.01686958e-01   9.60027533e-01]
 ..., 
 [ -1.83857075e-01  -2.36728755e-01  -3.85872803e-01 ...,   9.20771289e-02
   -5.96252826e-01  -3.29412526e-01]
 [ -2.74508389e-01  -1.79526875e-01  -1.76654948e-01 ...,  -1.16649856e-01
   -1.33863846e-01  -3.58682868e-01]
 [  3.90134314e-02   8.37951835e-02  -3.99823150e-02 ...,   5.30692327e-02
    2.91021290e+00  -7.95418544e-02]]
Progress: 81.7% ... Training loss: 0.062 ... Validation loss: 0.137[[-0.16010223]
 [-0.95098313]
 [-1.19383605]
 [-0.76339455]
 [-0.05688564]
 [ 2.65114767]
 [-0.05038027]
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 [ 1.04197157]
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 [ 0.14189936]
 [-0.10143322]
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 [-0.30189055]
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 [ 0.14385654]
 [-0.3525849 ]
 [ 4.49475924]
 [-0.947784  ]
 [-1.64534793]
 [ 0.38268284]
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 [ 4.32523691]
 [-1.93386193]]
[[ -1.95563433e-02  -3.07193967e-01   2.69713951e-01 ...,  -2.32957943e-01
   -3.22524876e-01   2.90655013e-01]
 [  5.82226620e-02   1.44869052e-01  -2.49473011e-03 ...,  -2.22606356e-01
    1.63597450e+00   1.13246801e-01]
 [ -5.91032719e-02   2.68902277e-01   4.76466096e-01 ...,   2.40975116e-01
   -2.95034550e-01   9.58225592e-01]
 ..., 
 [ -1.83877869e-01  -2.36824620e-01  -3.85936364e-01 ...,   9.20407073e-02
   -5.95474807e-01  -3.29708952e-01]
 [ -2.74540747e-01  -1.79712613e-01  -1.76902256e-01 ...,  -1.16705358e-01
   -1.33117019e-01  -3.59012176e-01]
 [  3.90723483e-02   8.41019517e-02  -3.96302717e-02 ...,   5.31693625e-02
    2.91007312e+00  -7.90303060e-02]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16342488]
 [-0.9542102 ]
 [-1.19543032]
 [-0.76783323]
 [-0.060525  ]
 [ 2.64970694]
 [-0.05362423]
 [-1.10562944]
 [-0.53237627]
 [ 1.04113326]
 [-0.09780827]
 [ 0.13905444]
 [-0.10534571]
 [-1.01687415]
 [-0.30504304]
 [ 0.86376543]
 [-0.84115529]
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 [ 0.14032407]
 [-0.35486255]
 [ 4.49443698]
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 [ 0.38075704]
 [-0.30954957]
 [ 4.31961895]
 [-1.93580428]]
[[ -1.94349980e-02  -3.06547198e-01   2.70139757e-01 ...,  -2.32731888e-01
   -3.22550377e-01   2.91495565e-01]
 [  5.81719935e-02   1.44573469e-01  -2.89782749e-03 ...,  -2.22694802e-01
    1.63706629e+00   1.12630940e-01]
 [ -5.91138032e-02   2.68888330e-01   4.76573718e-01 ...,   2.40991745e-01
   -2.94351044e-01   9.58555559e-01]
 ..., 
 [ -1.83887611e-01  -2.36879818e-01  -3.85995312e-01 ...,   9.20149461e-02
   -5.95346312e-01  -3.29898041e-01]
 [ -2.74529126e-01  -1.79626030e-01  -1.76845758e-01 ...,  -1.16677058e-01
   -1.32937328e-01  -3.58696524e-01]
 [  3.91764111e-02   8.46792392e-02  -3.91366197e-02 ...,   5.33544983e-02
    2.91000082e+00  -7.86199105e-02]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.137[[-0.1601707 ]
 [-0.95090559]
 [-1.19502928]
 [-0.76319149]
 [-0.05654448]
 [ 2.65188091]
 [-0.05024343]
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 [ 1.04265366]
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 [ 0.14212409]
 [-0.101583  ]
 [-1.01506717]
 [-0.30199061]
 [ 0.86673815]
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 [ 0.14325225]
 [-0.35208285]
 [ 4.49506709]
 [-0.94777152]
 [-1.64635877]
 [ 0.38296167]
 [-0.3064953 ]
 [ 4.32501527]
 [-1.93515259]]
[[-0.0194315  -0.3065141   0.27051153 ..., -0.23272399 -0.32268814
   0.29158033]
 [ 0.0581267   0.14433994 -0.00299284 ..., -0.22277571  1.63734958
   0.11241895]
 [-0.05906333  0.26918157  0.47616832 ...,  0.24107682 -0.29597717
   0.95809052]
 ..., 
 [-0.18386182 -0.23674867 -0.3857912  ...,  0.09205813 -0.59580275
  -0.32942026]
 [-0.27453644 -0.17966293 -0.1769347  ..., -0.11669001 -0.13281189
  -0.35891802]
 [ 0.03914787  0.08449254 -0.03895128 ...,  0.05330381  2.91014613
  -0.0789211 ]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.140[[-0.16551409]
 [-0.9554795 ]
 [-1.19862124]
 [-0.7686377 ]
 [-0.06131906]
 [ 2.65008143]
 [-0.05470565]
 [-1.10576338]
 [-0.53468889]
 [ 1.04047801]
 [-0.09938016]
 [ 0.13795096]
 [-0.10593094]
 [-1.0186622 ]
 [-0.30662841]
 [ 0.86208925]
 [-0.84304613]
 [-0.80148898]
 [-0.6243637 ]
 [ 0.13862816]
 [-0.35567449]
 [ 4.49423521]
 [-0.95263089]
 [-1.65075354]
 [ 0.37948797]
 [-0.31081128]
 [ 4.31703504]
 [-1.93768196]]
[[-0.0192088  -0.30520938  0.27145813 ..., -0.23230245 -0.32390882
   0.2938293 ]
 [ 0.05813392  0.14437951 -0.00297934 ..., -0.2227623   1.63729461
   0.11244221]
 [-0.05898579  0.2696842   0.4768111  ...,  0.24121676 -0.29560664
   0.95959733]
 ..., 
 [-0.18384365 -0.23665892 -0.38595205 ...,  0.09209408 -0.59631521
  -0.32941774]
 [-0.27447508 -0.17932269 -0.17658641 ..., -0.11657919 -0.13388663
  -0.35860312]
 [ 0.03913598  0.08442963 -0.03900028 ...,  0.05328882  2.91023575
  -0.07886222]]
Progress: 81.7% ... Training loss: 0.063 ... Validation loss: 0.137[[-0.1604238 ]
 [-0.95202254]
 [-1.19542454]
 [-0.7656019 ]
 [-0.05815633]
 [ 2.65249168]
 [-0.05101961]
 [-1.10291448]
 [-0.53079992]
 [ 1.04329454]
 [-0.09553351]
 [ 0.14182841]
 [-0.10186793]
 [-1.01613052]
 [-0.30217132]
 [ 0.86661883]
 [-0.83834196]
 [-0.79718569]
 [-0.62110478]
 [ 0.14250412]
 [-0.35183822]
 [ 4.49436439]
 [-0.94928886]
 [-1.64611108]
 [ 0.3826167 ]
 [-0.30751194]
 [ 4.32458745]
 [-1.93594231]]
[[-0.0193621  -0.30611056  0.27075893 ..., -0.23259445 -0.32292323
   0.29297633]
 [ 0.05810327  0.14420177 -0.00311947 ..., -0.22281601  1.63744666
   0.11221488]
 [-0.05899169  0.26949957  0.47652426 ...,  0.24118543 -0.29595572
   0.958832  ]
 ..., 
 [-0.18381076 -0.23647258 -0.38577109 ...,  0.09215772 -0.59648757
  -0.32896254]
 [-0.27446265 -0.17924563 -0.17655924 ..., -0.11655758 -0.1339247
  -0.35842129]
 [ 0.03899079  0.0836195  -0.03964794 ...,  0.05301906  2.91052538
  -0.08005529]]
Progress: 81.7% ... Training loss: 0.061 ... Validation loss: 0.139[[-0.16377063]
 [-0.95524098]
 [-1.19719061]
 [-0.7692633 ]
 [-0.06198325]
 [ 2.65221945]
 [-0.05382624]
 [-1.10683923]
 [-0.533165  ]
 [ 1.04032897]
 [-0.09874783]
 [ 0.13873862]
 [-0.10582286]
 [-1.01783441]
 [-0.3053991 ]
 [ 0.86309893]
 [-0.84164544]
 [-0.80007568]
 [-0.62284714]
 [ 0.13911732]
 [-0.35507617]
 [ 4.49342999]
 [-0.95238842]
 [-1.65052349]
 [ 0.38042122]
 [-0.31034327]
 [ 4.31863313]
 [-1.93682379]]
[[-0.0193306  -0.30590473  0.27116455 ..., -0.23255224 -0.32341609
   0.29299001]
 [ 0.05810112  0.14418871 -0.00305218 ..., -0.22282142  1.63737959
   0.11217441]
 [-0.05911009  0.26873942  0.47625267 ...,  0.24092255 -0.295811
   0.95854854]
 ..., 
 [-0.18383777 -0.2366269  -0.38594761 ...,  0.09210799 -0.59582726
  -0.32918385]
 [-0.27432657 -0.17848196 -0.17573789 ..., -0.11632649 -0.13561357
  -0.35729805]
 [ 0.03899736  0.08367311 -0.03965133 ...,  0.0530246   2.91068685
  -0.0807395 ]]
Progress: 81.7% ... Training loss: 0.062 ... Validation loss: 0.136[[-0.15779451]
 [-0.95000936]
 [-1.19134198]
 [-0.76517719]
 [-0.05758467]
 [ 2.65515535]
 [-0.04955891]
 [-1.10361317]
 [-0.52756285]
 [ 1.04487424]
 [-0.09400943]
 [ 0.14369817]
 [-0.10050426]
 [-1.01464174]
 [-0.29949611]
 [ 0.86941576]
 [-0.8354987 ]
 [-0.79448554]
 [-0.61706954]
 [ 0.14414946]
 [-0.34975163]
 [ 4.49531561]
 [-0.9489559 ]
 [-1.64554537]
 [ 0.38450247]
 [-0.30558109]
 [ 4.32823421]
 [-1.93461982]]
[[ -1.95957377e-02  -3.07432340e-01   2.69528108e-01 ...,  -2.33034934e-01
   -3.21026302e-01   2.90364243e-01]
 [  5.81482413e-02   1.44465464e-01  -2.89940224e-03 ...,  -2.22743357e-01
    1.63723410e+00   1.12492078e-01]
 [ -5.92881722e-02   2.67625852e-01   4.75233110e-01 ...,   2.40581241e-01
   -2.93802437e-01   9.56298743e-01]
 ..., 
 [ -1.83849315e-01  -2.36687319e-01  -3.86037535e-01 ...,   9.20791712e-02
   -5.95489629e-01  -3.29022983e-01]
 [ -2.74355418e-01  -1.78662734e-01  -1.75965951e-01 ...,  -1.16368886e-01
   -1.35691290e-01  -3.57517804e-01]
 [  3.89919751e-02   8.36247587e-02  -3.96576257e-02 ...,   5.30050369e-02
    2.91070085e+00  -8.10304240e-02]]
Progress: 81.7% ... Training loss: 0.063 ... Validation loss: 0.141[[-0.1644298 ]
 [-0.95631814]
 [-1.19632436]
 [-0.77154409]
 [-0.06374735]
 [ 2.6513006 ]
 [-0.05554123]
 [-1.10909072]
 [-0.53368029]
 [ 1.04153392]
 [-0.09983904]
 [ 0.13804565]
 [-0.1070988 ]
 [-1.01880831]
 [-0.30610674]
 [ 0.86253199]
 [-0.8422141 ]
 [-0.79866862]
 [-0.62310669]
 [ 0.13844396]
 [-0.35526195]
 [ 4.49417957]
 [-0.95377398]
 [-1.65124202]
 [ 0.37973978]
 [-0.31208779]
 [ 4.31740451]
 [-1.9375066 ]]
[[ -1.93662405e-02  -3.06113838e-01   2.71055554e-01 ...,  -2.32603459e-01
   -3.24099078e-01   2.92677753e-01]
 [  5.81734352e-02   1.44594052e-01  -2.65712284e-03 ...,  -2.22697791e-01
    1.63693410e+00   1.12698093e-01]
 [ -5.91402094e-02   2.68471679e-01   4.76699857e-01 ...,   2.40855572e-01
   -2.95513414e-01   9.59220583e-01]
 ..., 
 [ -1.83796941e-01  -2.36380063e-01  -3.85754818e-01 ...,   9.21763927e-02
   -5.96087991e-01  -3.28776867e-01]
 [ -2.74382684e-01  -1.78806017e-01  -1.76116880e-01 ...,  -1.16405605e-01
   -1.34662698e-01  -3.57766491e-01]
 [  3.91044215e-02   8.42432202e-02  -3.90143639e-02 ...,   5.32064875e-02
    2.91055473e+00  -8.01289663e-02]]
Progress: 81.7% ... Training loss: 0.063 ... Validation loss: 0.136

plt.plot(losses['train'], label='Training loss')
plt.plot(losses['validation'], label='Validation loss')
plt.legend()
_ = plt.ylim()

Check out your predictions

Here, use the test data to view how well your network is modeling the data. If something is completely wrong here, make sure each step in your network is implemented correctly.

fig, ax = plt.subplots(figsize=(8,4))

mean, std = scaled_features['cnt']
predictions = network.run(test_features).T*std + mean
ax.plot(predictions[0], label='Prediction')
ax.plot((test_targets['cnt']*std + mean).values, label='Data')
ax.set_xlim(right=len(predictions))
ax.legend()

dates = pd.to_datetime(rides.ix[test_data.index]['dteday'])
dates = dates.apply(lambda d: d.strftime('%b %d'))
ax.set_xticks(np.arange(len(dates))[12::24])
_ = ax.set_xticklabels(dates[12::24], rotation=45)

OPTIONAL: Thinking about your results(this question will not be evaluated in the rubric).

Answer these questions about your results. How well does the model predict the data? Where does it fail? Why does it fail where it does?

Note: You can edit the text in this cell by double clicking on it. When you want to render the text, press control + enter

Your answer below

I'm a bit confused about the output function.

sigmoid.. ReLU.. and f(x)=x? umm,,,

And there seems to be a little ambiguity about the optimization.

I tried several times to lower the validation loss below 0.2, but it failed.

I don't know which hyperparameter values are the best.

---

umm.....